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15 pages, 5523 KiB

Open AccessArticle

Developing and Field Testing Path Planning for Robotic Aquaculture Water Quality Monitoring

by Anthony Davis, Paul S. Wills, James E. Garvey, William Fairman, Md Arshadul Karim and Bing Ouyang

Appl. Sci. 2023, 13(5), 2805; https://doi.org/10.3390/app13052805 - 22 Feb 2023

Cited by 12 | Viewed by 3155

Abstract

Marine food chains are highly stressed by aggressive fishing practices and environmental damage. Aquaculture has increasingly become a source of seafood which spares the deleterious impact on wild fisheries. However, continually monitoring water quality to successfully grow and harvest fish is labor intensive. [...] Read more.

Marine food chains are highly stressed by aggressive fishing practices and environmental damage. Aquaculture has increasingly become a source of seafood which spares the deleterious impact on wild fisheries. However, continually monitoring water quality to successfully grow and harvest fish is labor intensive. The Hybrid Aerial Underwater Robotic System (HAUCS) is an Internet of Things (IoT) framework for aquaculture farms to relieve the farm operators of one of the most labor-intensive and time-consuming farm operations: water quality monitoring. To this end, HAUCS employs a swarm of unmanned aerial vehicles (UAVs) or drones integrated with underwater measurement devices to collect the in situ water quality data from aquaculture ponds. A critical aspect in HAUCS is to develop an effective path planning algorithm to be able to sample all the ponds on the farm with minimal resources (i.e., the number of UAVs and the power consumption of each UAV). Three methods of path planning for the UAVs are tested, a Graph Attention Model (GAM), the Google Linear Optimization Package (GLOP) and our proposed solution, the HAUCS Path Planning Algorithm (HPP). The designs of these path planning algorithms are discussed, and a simulator is developed to evaluate these methods’ performance. The algorithms are also experimentally validated at Southern Illinois University’s Aquaculture Research Center to demonstrate the feasibility of HAUCS. Based on the simulations and experimental studies, HPP is particularly suited for large farms, while GLOP or GAM is more suited to small or medium-sized farms. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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21 pages, 31116 KiB

Open AccessArticle

Measurement and Modeling of a Cargo Bicycle Tire for Vehicle Dynamics Simulation

by Marius Miller, Markus Pfeil, Benedikt Reick, Raphael Murri, Ralf Stetter and Ralph Kennel

Appl. Sci. 2023, 13(4), 2542; https://doi.org/10.3390/app13042542 - 16 Feb 2023

Cited by 5 | Viewed by 2816

Abstract

In the field of inner-city cargo transportation, solutions such as electrified cargo trailers are increasingly being used. To provide an intelligent drivetrain control system that improves driving dynamics and enables safety, it is necessary to know the characteristics of the trailer system. This [...] Read more.

In the field of inner-city cargo transportation, solutions such as electrified cargo trailers are increasingly being used. To provide an intelligent drivetrain control system that improves driving dynamics and enables safety, it is necessary to know the characteristics of the trailer system. This includes the behavior of the tires. Existing investigations of bicycle tires focus on camber-angle-dependent models. However, in most trailers, a rigid mounting of the tires without camber is used. For this reason, a bicycle tire model is created within the scope of this study using real measurement data that represent a 20 in tire with typical wheel loads and without camber. The measurements were collected with the mobile tire measurement laboratory of the Bern University of Applied Sciences on an asphalt test site under real conditions. Crosstalk occurring in the measurement hub during the data collection was successfully corrected using a matrix method. With help of the so-called Magic Formula, a tire model was created that can be used for driving dynamics simulations and controller design. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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27 pages, 17252 KiB

Open AccessArticle

Robust Adaptive Finite-Time Synergetic Tracking Control of Delta Robot Based on Radial Basis Function Neural Networks

by Phu-Cuong Pham and Yong-Lin Kuo

Appl. Sci. 2022, 12(21), 10861; https://doi.org/10.3390/app122110861 - 26 Oct 2022

Cited by 8 | Viewed by 3080

Abstract

This paper presents a robust proportional derivative adaptive nonsingular finite-time synergetic tracking control (PDAFS) for a parallel Delta robot system. First, a finite-time synergetic controller combined with a proportional derivative (PD) control is constructed based on an object-oriented model to fulfill the robust [...] Read more.

This paper presents a robust proportional derivative adaptive nonsingular finite-time synergetic tracking control (PDAFS) for a parallel Delta robot system. First, a finite-time synergetic controller combined with a proportional derivative (PD) control is constructed based on an object-oriented model to fulfill the robust tracking control of the robot. Then, an adaptive radial basis function approximation neural network (RBF) is designed to compensate for the effects of uncertainty parameters and external disturbances. Second, a second-order sliding mode (SOSM) differentiator is implemented to reduce the chattering noises due to the low-resolution encoders. Third, the stability theorems of the proposed control scheme are provided, where the Lyapunov stability theory is used to prove the theorems. Then, simulations of the helix trajectory tracking and the pick-and-place task are demonstrated on the Delta robot to validate the advantages of the proposed control scheme. Based on the advances, an implementing control system of the proposed controller is performed to improve the Delta robot’s performance in the experiments. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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18 pages, 4202 KiB

Open AccessArticle

Human-Centered Dynamic Service Scheduling Approach in Multi-Agent Environments

by Yunseo Jung, Hyunju Kim, Kyung-Duk Suh and Jung-Min Park

Appl. Sci. 2022, 12(21), 10850; https://doi.org/10.3390/app122110850 - 26 Oct 2022

Cited by 2 | Viewed by 1670

Abstract

As robots become more versatile and combined with a variety of Internet-of-Things technologies, they will be able to serve humans in their daily environments. To provide services by satisfying various human requests, several robots must take turns performing a series of tasks that [...] Read more.

As robots become more versatile and combined with a variety of Internet-of-Things technologies, they will be able to serve humans in their daily environments. To provide services by satisfying various human requests, several robots must take turns performing a series of tasks that constitute the service. Because the order of service delivery may differ according to user requests, sequential interdependencies between tasks should be considered. Therefore, we propose a dynamic service scheduler consisting of dynamic sequencing and allocation that can handle scheduling of tasks with user requests such as prioritizing certain tasks or actively changing their order in a multi-agent environment. We experimented with the proposed method in four situation scenarios by building a virtual reality smart office consisting of multiple robots with a robot arm, mobile robot, and smart lamp. The results demonstrated the feasibility and effectiveness of the proposed approach by satisfying the user requirements in different situations. The proposed approach constitutes a basis for further development of efficient in-office and at-home multi-agent environments. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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17 pages, 2911 KiB

Open AccessArticle

A Development of Optimal Algorithm for Integrated Operation of UGVs and UAVs for Goods Delivery at Tourist Destinations

by Young Kwan Ko, Ju Hyeong Park and Young Dae Ko

Appl. Sci. 2022, 12(20), 10396; https://doi.org/10.3390/app122010396 - 15 Oct 2022

Cited by 6 | Viewed by 1554

Abstract

Although the actual use of delivery robots like UGVs and UAVs has not yet been generalized, they are also used for additional purposes like fun and enjoyment in some limited areas such as tourist destinations. In this study, an optimal algorithm is proposed [...] Read more.

Although the actual use of delivery robots like UGVs and UAVs has not yet been generalized, they are also used for additional purposes like fun and enjoyment in some limited areas such as tourist destinations. In this study, an optimal algorithm is proposed that operates a delivery service through an integrated system of UGVs and UAVs at certain tourism destination. It is assumed that both UGVs and UAVs or only one means could be used depending on the type of goods delivered and the topographical characteristics. The mathematical model-based optimization technique is applied to generate the delivery service route of both UGVs and UAVs that can maximize total customer satisfaction. The developed mathematical model is solved through CPLEX and genetic algorithm, and the results are compared by dividing into case 1 in which UAVs move freely and case 2 in which UAVs can move only in a limited path since there is a risk of accidental falling when moving. As a result, when UAVs move freely, the total customer satisfaction is higher while the total complete time increases. However, it is suggested that an appropriate operation policy should be determined considering the risk of accidental falling. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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28 pages, 2344 KiB

Open AccessArticle

Balance Control of a Configurable Inverted Pendulum on an Omni-Directional Wheeled Mobile Robot

by Sho-Tsung Kao and Ming-Tzu Ho

Appl. Sci. 2022, 12(20), 10307; https://doi.org/10.3390/app122010307 - 13 Oct 2022

Cited by 2 | Viewed by 2722

Abstract

This paper considers the balance control problems of a configurable inverted pendulum with an omni-directional wheeled mobile robot. The system consists of two parts. One is an inverted pendulum, and another one is an omni-directional wheeled mobile robot. The system can be configured [...] Read more.

This paper considers the balance control problems of a configurable inverted pendulum with an omni-directional wheeled mobile robot. The system consists of two parts. One is an inverted pendulum, and another one is an omni-directional wheeled mobile robot. The system can be configured as a rotary inverted pendulum or a spherical inverted pendulum. The objective is to control the omni-directional wheeled mobile robot to provide translational force on the plane to balance the spherical inverted pendulum and to provide the moment to balance the rotary inverted pendulum. Detailed dynamic models of these two systems are derived for the control strategy design and simulation studies. Stabilizing controllers based on the second-order sliding mode control are designed for both systems. The closed-loop stability is proved based on the passivity properties. The proposed control schemes can guarantee semi-globally asymptotical stability over the upper-half plane. In addition, the conventional sliding mode controllers proposed in our previous work and Linear-Quadratic Regulator (LQR) controllers based on the linearized system models about its upright equilibrium point are also used for performance comparison. The effectiveness of the control strategies is investigated and verified using simulation and experimental studies. In the simulation studies, different sources of uncertainty and disturbance are investigated. It is shown that the second-order sliding mode control outperforms the conventional sliding mode control and LQR control without any uncertainty and disturbance. For robustness to the matched disturbance, the simulation results show that the second-order sliding mode controller has a less significant steady-state oscillation in the pendulum’s angular displacement than other controllers. The simulation results also show that only the second-order sliding mode controller can stabilize the system with a significant initial deviation from the pendulum’s upright position. Finally, the experimental results demonstrate that second-order sliding mode control outperforms conventional sliding mode control and LQR control. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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25 pages, 8554 KiB

Open AccessArticle

A Quasi-Velocity-Based Tracking Controller for a Class of Underactuated Marine Vehicles

by Przemyslaw Herman

Appl. Sci. 2022, 12(17), 8903; https://doi.org/10.3390/app12178903 - 5 Sep 2022

Cited by 2 | Viewed by 1636

Abstract

This paper investigates the trajectory tracking control problem for underactuated underwater vehicles, for which a model is expressed in terms of quasi-velocities arising from the inertia matrix decomposition. The control approach takes into account non-modeled dynamics and external disturbances and is suitable for [...] Read more.

This paper investigates the trajectory tracking control problem for underactuated underwater vehicles, for which a model is expressed in terms of quasi-velocities arising from the inertia matrix decomposition. The control approach takes into account non-modeled dynamics and external disturbances and is suitable for symmetric vehicles. It is shown that such systems can be diagonalized using inertial quasi-velocities (IQVs). The strategy consists of the velocity controller and two adaptive integral sliding mode control algorithms. The proposed approach, introducing velocity transformation and using backstepping methods and integral sliding mode control, allows trajectory tracking for vehicles in described models with symmetric inertia matrix. Proof of the stability of the closed system was carried out using IQV. The proposed scheme has been verified on two 3 DOF models of underwater vehicles with thruster limitations. A brief discussion of the results is also given. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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16 pages, 3014 KiB

Open AccessArticle

Enhanced Search-and-Rescue Optimization-Enabled Secure Route Planning Scheme for Internet of Drones Environment

by Fatma S. Alrayes, Sami Dhahbi, Jaber S. Alzahrani, Amal S. Mehanna, Mesfer Al Duhayyim, Abdelwahed Motwakel, Ishfaq Yaseen and Amgad Atta Abdelmageed

Appl. Sci. 2022, 12(15), 7950; https://doi.org/10.3390/app12157950 - 8 Aug 2022

Cited by 4 | Viewed by 2041

Abstract

The Internet of Drones (IoD) is greatly developed and promotes many civil applications. However, it can still be prone to several security problems which threaten public safety. The issue of security poses further problems upon linking the IoD to the Internet, as its [...] Read more.

The Internet of Drones (IoD) is greatly developed and promotes many civil applications. However, it can still be prone to several security problems which threaten public safety. The issue of security poses further problems upon linking the IoD to the Internet, as its data stream is exposed to attack. For secure communication between drones, an effective route planning scheme with a major intention of accomplishing security is needed. With this aim, this study develops an enhanced search-and-rescue optimization-enabled secure route planning (ESRO-SRP) scheme for the IoD environment. The presented ESRO-SRP technique mainly aims to derive a set of optimal routes to the destination. In addition, the ESRO-SRP algorithm is derived by the integration of the quasi-oppositional-based learning (QOBL) concept with the conventional SRO algorithm. Moreover, the presented ESRO-SRP technique derived a fitness function encompassing different input parameters such as residual energy, distance, and degree of trust. The experimental validation of the ESRO-SRP technique is carried out under several aspects, and the results demonstrated the enhancements of the ESRO-SRP model over recent approaches. The ESRO-SRP model has provided an increased packet delivery ratio (PDR) of 86%, whereas the BRUe-IoE, ORP-FANET, UAVe-WSN, and TR-UAV Swarm approaches have accomplished a minimal PDR of 79.60%, 73.60%, 67.60%, and 63.20%, respectively. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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17 pages, 928 KiB

Open AccessArticle

A Neural Network-Based Navigation Approach for Autonomous Mobile Robot Systems

by Yiyang Chen, Chuanxin Cheng, Yueyuan Zhang, Xinlin Li and Lining Sun

Appl. Sci. 2022, 12(15), 7796; https://doi.org/10.3390/app12157796 - 3 Aug 2022

Cited by 29 | Viewed by 3508

Abstract

A mobile robot is a futuristic technology that is changing the industry of automobiles as well as boosting the operations of on-demand services and applications. The navigation capability of mobile robots is a crucial task and one of the complex processes that guarantees [...] Read more.

A mobile robot is a futuristic technology that is changing the industry of automobiles as well as boosting the operations of on-demand services and applications. The navigation capability of mobile robots is a crucial task and one of the complex processes that guarantees moving from a starting position to a destination. To prevent any potential incidents or accidents, navigation must focus on the obstacle avoidance issue. This paper considers the navigation scenario of a mobile robot with a finite number of motion types without global environmental information. In addition, appropriate human decisions on motion types were collected in situations involving various obstacle features, and the corresponding environmental information was also recorded with the human decisions to establish a database. Further, an algorithm is proposed to train a neural network model via supervising learning using the collected data to replicate the human decision-making process under the same navigation scenario. The performance of the neural network-based decision-making method was cross-validated using both training and testing data to show an accuracy level close to

90 %

. In addition, the trained neural network model was installed on a virtual mobile robot within a mobile robot navigation simulator to interact with the environment and to make the decisions, and the results showed the effectiveness and efficacy of the proposed algorithm. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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11 pages, 1075 KiB

Open AccessArticle

Autonomous Driving Control Based on the Perception of a Lidar Sensor and Odometer

by Jichiang Tsai, Che-Cheng Chang, Yu-Cheng Ou, Bing-Herng Sieh and Yee-Ming Ooi

Appl. Sci. 2022, 12(15), 7775; https://doi.org/10.3390/app12157775 - 2 Aug 2022

Cited by 6 | Viewed by 2456

Abstract

Recently, many artificial intelligence applications in smart cars have been utilized in real life. Making an unmanned ground vehicle (UGV) capable of moving autonomously has become a critical topic. Hence, in this work, a novel method for a UGV to realize path planning [...] Read more.

Recently, many artificial intelligence applications in smart cars have been utilized in real life. Making an unmanned ground vehicle (UGV) capable of moving autonomously has become a critical topic. Hence, in this work, a novel method for a UGV to realize path planning and obstacle avoidance is presented using a deep deterministic policy gradient approach (DDPG). More specifically, the lidar sensor mounted on the vehicle is utilized to measure the distance between the vehicle and the surrounding obstacles, and the odometer measures the mileage of the vehicle for the purpose of estimating the current location. Then, the above sensed data are treated as the training data for the DDPG training procedure, and several experiments are performed in different settings utilizing the robot operating system (ROS) and the Gazebo simulator with a real robot module, TurtleBot3, to present a comprehensive discussion. The simulation results show that using the presented design and reward architecture, the DDPG method is better than the classic deep Q-network (DQN) method, e.g., taking fewer steps to reach the goal, less training time to find the smallest number of steps for reaching the goal, and so on. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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20 pages, 5671 KiB

Open AccessArticle

Distance Assessment by Object Detection—For Visually Impaired Assistive Mechatronic System

by Ciprian Dragne, Isabela Todiriţe, Mihaiela Iliescu and Marius Pandelea

Appl. Sci. 2022, 12(13), 6342; https://doi.org/10.3390/app12136342 - 22 Jun 2022

Cited by 7 | Viewed by 2557

Abstract

Techniques for the detection and recognition of objects have experienced continuous development over recent years, as their application and benefits are so very obvious. Whether they are involved in driving a car, environment surveillance and security, or assistive living for people with different [...] Read more.

Techniques for the detection and recognition of objects have experienced continuous development over recent years, as their application and benefits are so very obvious. Whether they are involved in driving a car, environment surveillance and security, or assistive living for people with different disabilities, not to mention advanced robotic surgery, these techniques are almost indispensable. This article presents the research results of a distance assessment using object detection and recognition techniques. The first is a new technique based on low-cost photo cameras and special sign detection. The second is a classic approach based on a LIDAR sensor and an HQ photo camera. Its novelty, in this case, consists of the concept and prototype of the hardware subsystem for high-precision distance measurement, as well as fast and accurate object recognition. The experimentally obtained results are used for the motion control strategy (directional inverse kinematics) of the robotic arm (virtual prototype) component in special assistive devices designed for visually impaired persons. The advantages of the original technical solution, experimentally validated by a prototype system with modern equipment, are the precision and the short time required for the identification and recognition of objects at relatively short distances. The research results obtained, in both the real and virtual experiments, stand as a basis for the further development of the visually impaired mechatronic system prototype using additional ultrasonic sensors, stereoscopic or multiple cameras, and the implementation of machine-learning models for safety-critical tasks. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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15 pages, 5342 KiB

Open AccessArticle

Mobile Robot Control Based on 3D Visual Servoing: A New Approach Combining Pose Estimation by Neural Network and Differential Flatness

by Khaled Kaaniche, Osama El-Hamrawy, Nasr Rashid, Mohammed Albekairi and Hassen Mekki

Appl. Sci. 2022, 12(12), 6167; https://doi.org/10.3390/app12126167 - 17 Jun 2022

Cited by 1 | Viewed by 2086

Abstract

This paper deals with 3D visual servoing applied to mobile robots in the presence of measurement disturbances, caused in particular by target occlusion. We propose a new approach based on the flatness concept. In 3D visual servoing, the task is performed out of [...] Read more.

This paper deals with 3D visual servoing applied to mobile robots in the presence of measurement disturbances, caused in particular by target occlusion. We propose a new approach based on the flatness concept. In 3D visual servoing, the task is performed out of image coordinate space and targets may leave the camera field of view during navigation (servoing). Forced to navigate blindly during one or more periods of time, the robot will use our new open-loop control algorithm inspired by the flatness concept. The 3D visual servoing method is performed using robot pose estimation. This estimation generally contains some errors. The exact position of the robot is therefore not guaranteed, and robust feedback control is necessary to reject these errors in the input. To solve this problem, we propose a new pose estimation method that uses neural networks. We reduce the complexity of the architecture of the neural networks used (the number of variables to estimate) by proving that the location and the orientation of the robot can be ensured by using a single point in the image coordinate space for mobile robots with two degrees of freedom. To show the efficiency of the proposed algorithm, we use the RVCTOOLS MATLAB toolbox. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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14 pages, 6113 KiB

Open AccessArticle

Noise Characteristics Analysis of Medical Electric Leg Compression Machine Using Multibody Dynamic Simulation

by Sungwook Kang, Hyunsoo Kim, Jaewoong Kim, Jong-Moon Hwang, Wonhee Lee, Jungtae Kim and Hyunsu Ryu

Appl. Sci. 2022, 12(8), 3977; https://doi.org/10.3390/app12083977 - 14 Apr 2022

Cited by 1 | Viewed by 1957

Abstract

Conventional medical equipment used for treating patients with ischemic heart disease relies on pneumatic compression to achieve intense and instantaneous compression of the legs. Because the pneumatic operation of a compressor inevitably produces noise, the treatment is given to a patient in a [...] Read more.

Conventional medical equipment used for treating patients with ischemic heart disease relies on pneumatic compression to achieve intense and instantaneous compression of the legs. Because the pneumatic operation of a compressor inevitably produces noise, the treatment is given to a patient in a separate room to avoid causing discomfort to other patients. This need for a dedicated treatment room could be another source of increased medical costs. In this study, a new electrical motor-driven system was developed to address the noise problem of existing pneumatic compression devices. Additionally, the new system features a reduced footprint and weight, and can be carried by medical staff. To develop a low-noise leg compression machine, the noise level at the surface of the structure was estimated using multibody dynamics simulation. Based on the initial design of the electric leg compression machine, parameters including assembly tolerance, component material, and shape of the structure were adjusted to prepare variations of the initial design, and their noise characteristics were analyzed. It was found that by applying the design variables, the noise levels were reduced by 7.2–11.7% compared with the initial design. The most significant reduction in noise levels was 11.7% and was achieved by reinforcing the section surrounding the gearbox enclosing a noise source. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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19 pages, 3227 KiB

Open AccessArticle

Multi-Robot Leader Grouping Consistent Formation Control Method Research with Low Convergence Time Based on Nonholonomic Constraints

by Hongchao Zhuang, Kailun Dong, Ning Wang and Lei Dong

Appl. Sci. 2022, 12(5), 2300; https://doi.org/10.3390/app12052300 - 22 Feb 2022

Cited by 8 | Viewed by 2981

Abstract

Aiming at the formation and maintenance of the multiple formations of nonholonomic constrained multi-robots, a leader-follower formation control method under the grouping consistency is proposed on the trajectory tracking of a nonholonomic constrained mobile robots with the low convergence time. The distributed control [...] Read more.

Aiming at the formation and maintenance of the multiple formations of nonholonomic constrained multi-robots, a leader-follower formation control method under the grouping consistency is proposed on the trajectory tracking of a nonholonomic constrained mobile robots with the low convergence time. The distributed control structure in the leader-follower formation is adopted. The multi-robot cooperative formation is realized by using the consistency algorithm of graph theory. According to the graph theory, the communication topology matrixes are designed by the consistency algorithm. The mathematical model of nonholonomic constrained robot is established with the wheeled structure as the mobile structure under the nonholonomic constraints. Then the navigation following model is transformed into the error model of a local coordinate system through the global coordinate transformation. The formation control law of multi-robot cooperative motion is put forward based on the leader-follower model. Its convergence is proved by the Lyapunov function. By setting the reasonable communication protocol parameters, the MATLAB software (Natick, MA, USA, R2016b) is employed on the simulation verification and result comparison. Through the comparison of the two leader formation control methods, the convergence time of the algorithm in this article can be 25% less than that of PFC. The effectiveness and feasibility of the formation control law are verified under the leader-follower method. The proposed control method lays a foundation for reducing the convergence time to improve the multi-robot cooperative motion under nonholonomic constraints. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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14 pages, 5256 KiB

Open AccessArticle

Development of a Control System for Multilink Manipulators on Unmanned Underwater Vehicles Dynamically Positioned over Seafloor Objects

by Alexander Konoplin, Alexander Yurmanov, Nikita Krasavin and Pavel Piatavin

Appl. Sci. 2022, 12(3), 1666; https://doi.org/10.3390/app12031666 - 5 Feb 2022

Cited by 15 | Viewed by 2034

Abstract

This article considers an approach to synthesizing a multilevel system to control movements of a multilink manipulator (MM) mounted on an unmanned underwater vehicle (UUV) for performing autonomous manipulative operations in the mode of dynamic positioning over various objects on the seafloor. The [...] Read more.

This article considers an approach to synthesizing a multilevel system to control movements of a multilink manipulator (MM) mounted on an unmanned underwater vehicle (UUV) for performing autonomous manipulative operations in the mode of dynamic positioning over various objects on the seafloor. The system is based on an upgraded method that, using point clouds received from the machine vision systems (MVS), provides high-accuracy determination of the shape and location of the work object relative to UUV. The preset trajectories of the MM working tool are overlaid on the identified surface of the object, with possible silting, fouling or deformation of the latter taken into account. To execute the programmed trajectories with the MM working tool, the following methods have been implemented in software: stabilization of UUV in hovering mode near the object, high-precision control of working tool’s movements, and also corrections of its trajectory taking into account UUV’s displacements relative to the object. The synthesized system has been developed in the C++ programming language. The operation of the system has been numerically simulated using a model of UUV with MM, as well as models of the environment and the target object, in the Matlab/Simulink and V-REP software packages. The results of the study show a high efficiency of the system both in processing sensor information and in providing the dynamic control of movements of an UUV with a MM. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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15 pages, 678 KiB

Open AccessArticle

Intelligent Trust-Based Utility and Reusability Model: Enhanced Security Using Unmanned Aerial Vehicles on Sensor Nodes

by Santosh Kumar Sahoo, Niranjanamurthy Mudligiriyappa, Abdullah A. Algethami, Poongodi Manoharan, Mounir Hamdi and Kaamran Raahemifar

Appl. Sci. 2022, 12(3), 1317; https://doi.org/10.3390/app12031317 - 26 Jan 2022

Cited by 36 | Viewed by 3239

Abstract

Due to its importance in prolonging the lifetime of battery-restricted wireless sensor networks, network longevity has garnered considerable research attention, with the rechargeable wireless sensor network emerging as a viable solution. In this research, the novel methodology of a trust-based mechanism for enhanced [...] Read more.

Due to its importance in prolonging the lifetime of battery-restricted wireless sensor networks, network longevity has garnered considerable research attention, with the rechargeable wireless sensor network emerging as a viable solution. In this research, the novel methodology of a trust-based mechanism for enhanced security integrated with an energy utility and re-usability model is proposed with software-defined networking (SDN) to maximize energy utilization. We proposed a novel framework with SDN for the service station in a wireless sensor network (WSN). The results showed that the life capacity of the network increases to a maximum of 290% when compared with no charging, with the charge increasing by 30% intervals. We also present how the network survives through this choice of sink. As there is variation in the network size while it increases, the proposed approach with the static method works well until the network size reaches 200. Furthermore, the proposed approach also uses the heuristic method to achieve the best performance. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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15 pages, 4876 KiB

Open AccessArticle

The Kinematic Analysis of a Wind Turbine Climbing Robot Mechanism

by Jui-Hung Liu and Kathleen Ebora Padrigalan

Appl. Sci. 2022, 12(3), 1210; https://doi.org/10.3390/app12031210 - 24 Jan 2022

Cited by 5 | Viewed by 3269

Abstract

The emergence of renewable energy offers opportunities for academia and the industry to conduct scientific research and innovative technological developments on wind turbine climbing robots. These robots were developed to carry out specialized application tasks, such as in-situ inspection and maintenance of wind [...] Read more.

The emergence of renewable energy offers opportunities for academia and the industry to conduct scientific research and innovative technological developments on wind turbine climbing robots. These robots were developed to carry out specialized application tasks, such as in-situ inspection and maintenance of wind turbine physical structure. This paper presents a scaled-down prototype design of a climbing robot for wind turbine maintenance and its kinematic modeling. The winding mechanism is the key feature for providing enough adhesion force to support the climbing robot and needs to adapt to the different diameters of the wind turbine tower, as it climbs through a circular truncated cone shape. A climbing model is then considered, using four mecanum wheels for maneuverability of the different movement states up-down, rotation, and spiral as it climbs the wind turbine tower. The design of the wind turbine climbing robot was modeled in SketchUp and the motion states were implemented in MATLAB for the climbing performance capabilities of the driving wheels of the robot. Based on the theoretical results of motion characteristics, the scaled-down prototype design of a climbing robot possesses maneuverability of motion and is able to predict the robot’s performance. The contribution of this paper is intended to provide a basis for the new transformative climbing robot design and effectiveness of the mecanum wheel for robot motion. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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19 pages, 6885 KiB

Open AccessArticle

Analyzing Dynamic Operational Conditions of Limb Prosthetic Sockets with a Mechatronics-Twin Framework

by Dejiu Chen, Peng Su, Suranjan Ottikkutti, Panagiotis Vartholomeos, Kaveh Nazem Tahmasebi and Michalis Karamousadakis

Appl. Sci. 2022, 12(3), 986; https://doi.org/10.3390/app12030986 - 19 Jan 2022

Cited by 7 | Viewed by 3051

Abstract

Lower limb prostheses offer a solution to restore the ambulation and self-esteem of amputees. One key component is the prosthetic socket that serves as the interface between prosthetic device and amputee stump and thereby has a wide range of impacts on efficient fitting, [...] Read more.

Lower limb prostheses offer a solution to restore the ambulation and self-esteem of amputees. One key component is the prosthetic socket that serves as the interface between prosthetic device and amputee stump and thereby has a wide range of impacts on efficient fitting, appropriate load transmission, operational stability, and control. For the design and optimization of a prosthetic socket, an understanding of the actual intra-socket operational conditions becomes therefore necessary. This is however a difficult task due to the inherent complexity and restricted observability of socket operation. In this study, an innovative mechatronics-twin framework that integrates advanced biomechanical models and simulations with physical prototyping and dynamic operation testing for effective exploration of operational behaviors of prosthetic sockets with amputees is proposed. Within this framework, a specific Stewart manipulator is developed to enable dynamic operation testing, in particular for a well-managed generation of dynamic intra-socket loads and behaviors that are otherwise difficult to observe or realize with the real amputees. A combination of deep learning and Bayesian Inference algorithms is then employed for analyzing the intra-socket load conditions and revealing possible anomalous. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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19 pages, 9344 KiB

Open AccessArticle

Approach to Automated Visual Inspection of Objects Based on Artificial Intelligence

by Ivan Kuric, Jaromír Klarák, Vladimír Bulej, Milan Sága, Matej Kandera, Adrián Hajdučík and Karol Tucki

Appl. Sci. 2022, 12(2), 864; https://doi.org/10.3390/app12020864 - 15 Jan 2022

Cited by 14 | Viewed by 4610

Abstract

The article discusses the possibility of object detector usage in field of automated visual inspection for objects with specific parameters, specifically various types of defects occurring on the surface of a car tire. Due to the insufficient amount of input data, as well [...] Read more.

The article discusses the possibility of object detector usage in field of automated visual inspection for objects with specific parameters, specifically various types of defects occurring on the surface of a car tire. Due to the insufficient amount of input data, as well as the need to speed up the development process, the Transfer Learning principle was applied in a designed system. In this approach, the already pre-trained convolutional neural network AlexNet was used, subsequently modified in its last three layers, and again trained on a smaller sample of our own data. The detector used in the designed camera inspection system with the above architecture allowed us to achieve the accuracy and versatility needed to detect elements (defects) whose shape, dimensions and location change with each occurrence. The design of a test facility with the application of a 12-megapixel monochrome camera over the rotational table is briefly described, whose task is to ensure optimal conditions during the scanning process. The evaluation of the proposed control system with the quantification of the recognition capabilities in the individual defects is described at the end of the study. The implementation and verification of such an approach together with the proposed methodology of the visual inspection process of car tires to obtain better classification results for six different defect classes can be considered as the main novel feature of the presented research. Subsequent testing of the designed system on a selected batch of sample images (containing all six types of possible defect) proved the functionality of the entire system while the highest values of successful defect detection certainty were achieved from 85.15% to 99.34%. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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22 pages, 8291 KiB

Open AccessArticle

Modular Robotic Design and Reconfiguring Path Planning

by Ye Dai, Chao-Fang Xiang, Zhao-Xu Liu, Zhao-Long Li, Wen-Yin Qu and Qi-Hao Zhang

Appl. Sci. 2022, 12(2), 723; https://doi.org/10.3390/app12020723 - 12 Jan 2022

Cited by 6 | Viewed by 2439

Abstract

The modular robot is becoming a prevalent research object in robots because of its unique configuration advantages and performance characteristics. It is possible to form robot configurations with different functions by reconfiguring functional modules. This paper focuses on studying the modular robot’s configuration [...] Read more.

The modular robot is becoming a prevalent research object in robots because of its unique configuration advantages and performance characteristics. It is possible to form robot configurations with different functions by reconfiguring functional modules. This paper focuses on studying the modular robot’s configuration design and self-reconfiguration process and hopes to realize the industrial application of the modular self-reconfiguration robot to a certain extent. We design robotic configurations with different DOF based on the cellular module of the hexahedron and perform the kinematic analysis of the structure. An innovative design of a modular reconfiguration platform for conformational reorganization is presented, and the collaborative path planning between different modules in the reconfiguration platform is investigated. We propose an optimized ant colony algorithm for reconfiguration path planning and verify the superiority and rationality of this algorithm compared with the traditional ant colony algorithm for platform path planning through simulation experiments. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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16 pages, 32764 KiB

Open AccessArticle

Negotiating Uneven Terrain by a Simple Teleoperated Tracked Vehicle with Internally Movable Center of Gravity

by Yasuhiro Fukuoka, Kazuyuki Oshino and Ahmad Najmuddin Ibrahim

Appl. Sci. 2022, 12(1), 525; https://doi.org/10.3390/app12010525 - 5 Jan 2022

Cited by 6 | Viewed by 3302

Abstract

We propose a mechanical design for a simple teleoperated unmanned ground vehicle (UGV) to negotiate uneven terrain. UGVs are typically classified into legged, legged-wheeled, wheeled, and tanked forms. Legged vehicles can significantly shift their center of gravity (COG) by positioning their multi-articulated legs [...] Read more.

We propose a mechanical design for a simple teleoperated unmanned ground vehicle (UGV) to negotiate uneven terrain. UGVs are typically classified into legged, legged-wheeled, wheeled, and tanked forms. Legged vehicles can significantly shift their center of gravity (COG) by positioning their multi-articulated legs at appropriate trajectories, stepping over a high obstacle. To realize a COG movable mechanism with a small number of joints, a number of UGVs have been developed that can shift their COG by moving a mass at a high position above the body. However, these tend to pose a risk of overturning, and the mass must be moved quite far to climb a high step. To address these issues, we design a novel COG shift mechanism, in which the COG can be shifted forward and backward inside the body by moving most of its internal devices. Since this movable mass includes DC motors for driving both tracks, we can extend the range of the COG movement. We demonstrate that a conventional tracked vehicle prototype can traverse a step and a gap between two steps, as well as climb stairs and a steep slope, with a human operating the vehicle movement and the movable mass position. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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13 pages, 10579 KiB

Open AccessArticle

Reconfigurable/Foldable Overconstrained Mechanism and Its Application

by Lucian Matei, Mihaiela Iliescu, Ilie Dumitru, Mihaela Racila, Glencora-Maria Benec Mincu and Laurentiu Racila

Appl. Sci. 2022, 12(1), 262; https://doi.org/10.3390/app12010262 - 28 Dec 2021

Cited by 1 | Viewed by 1817

Abstract

The paper presents some possible applications started from a six revolute joints (6R) overconstrained mechanism. The spatial devices obtained are based on the 6R Wohlhart symmetric mechanism in a special spatial position, with three non-adjacent joints constrained to remain in a fixed plane. [...] Read more.

The paper presents some possible applications started from a six revolute joints (6R) overconstrained mechanism. The spatial devices obtained are based on the 6R Wohlhart symmetric mechanism in a special spatial position, with three non-adjacent joints constrained to remain in a fixed plane. This special spatial disposition allows us to obtain some reconfigurable/foldable devices, with an estimated application in the automotive industry field. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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17 pages, 1049 KiB

Open AccessArticle

Acceptance of Medical Treatment Regimens Provided by AI vs. Human

by Jiahua Wu, Liying Xu, Feng Yu and Kaiping Peng

Appl. Sci. 2022, 12(1), 110; https://doi.org/10.3390/app12010110 - 23 Dec 2021

Cited by 6 | Viewed by 4149

Abstract

Along with the increasing development of information technology, the interaction between artificial intelligence and humans is becoming even more frequent. In this context, a phenomenon called “medical AI aversion” has emerged, in which the same behaviors of medical AI and humans elicited different [...] Read more.

Along with the increasing development of information technology, the interaction between artificial intelligence and humans is becoming even more frequent. In this context, a phenomenon called “medical AI aversion” has emerged, in which the same behaviors of medical AI and humans elicited different responses. Medical AI aversion can be understood in terms of the way that people attribute mind capacities to different targets. It has been demonstrated that when medical professionals dehumanize patients—making fewer mental attributions to patients and, to some extent, not perceiving and treating them as full human—it leads to more painful and effective treatment options. From the patient’s perspective, will painful treatment options be unacceptable when they perceive the doctor as a human but disregard his or her own mental abilities? Is it possible to accept a painful treatment plan because the doctor is artificial intelligence? Based on the above, the current study investigated the above questions and the phenomenon of medical AI aversion in a medical context. Through three experiments it was found that: (1) human doctor was accepted more when patients were faced with the same treatment plan; (2) there was an interactional effect between the treatment subject and the nature of the treatment plan, and, therefore, affected the acceptance of the treatment plan; and (3) experience capacities mediated the relationship between treatment provider (AI vs. human) and treatment plan acceptance. Overall, this study attempted to explain the phenomenon of medical AI aversion from the mind perception theory and the findings are revealing at the applied level for guiding the more rational use of AI and how to persuade patients. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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21 pages, 7212 KiB

Open AccessArticle

Magnetically Deployable Robots Using Layered Lamina Emergent Mechanism

by Tran Nguyen Lam Giang, Catherine Jiayi Cai, Godwin Ponraj and Hongliang Ren

Appl. Sci. 2022, 12(1), 14; https://doi.org/10.3390/app12010014 - 21 Dec 2021

Cited by 3 | Viewed by 3019

Abstract

The steady rise of deployable structures and mechanisms based on kirigami and origami principles has brought about design innovations that yield flexible and lightweight robots. These robots are designed based on desirable locomotion mechanisms and often incorporate additional materials to support their flexible [...] Read more.

The steady rise of deployable structures and mechanisms based on kirigami and origami principles has brought about design innovations that yield flexible and lightweight robots. These robots are designed based on desirable locomotion mechanisms and often incorporate additional materials to support their flexible structure to enable load-bearing applications and considerable efficient movement. One tetherless way to actuate these robots is via the use of magnets. This paper incorporates magnetic actuation and kirigami structures based on the lamina emergent mechanism (LEM). Three designs of magnetic-actuated LEMs (triangular prism, single LEM (SLEM), alternating mirror dual LEM (AMDLEM)) are proposed, and small permanent magnets are attached to the structures’ flaps or legs that rotate in response to an Actuating Permanent Magnet (APM) to yield stick-slip locomotion, enabling the robots to waddle and crawl on a frictional surface. For preliminary characterization, we actuate the three designs at a frequency of 0.6 Hz. We observed the triangular prism, SLEM, and AMDLEM prototypes to achieve horizontal speeds of 4.3 mm/s, 10.7 mm/s, and 12.5 mm/s on flat surfaces, respectively. We further explore how changing different parameters (actuation frequency, friction, leg length, stiffness, compressibility) affects the locomotion of the different mechanisms. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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26 pages, 78047 KiB

Open AccessArticle

Using Brain-Computer Interface to Control a Virtual Drone Using Non-Invasive Motor Imagery and Machine Learning

by Catalin Dumitrescu, Ilona-Madalina Costea and Augustin Semenescu

Appl. Sci. 2021, 11(24), 11876; https://doi.org/10.3390/app112411876 - 14 Dec 2021

Cited by 15 | Viewed by 4399

Abstract

In recent years, the control of devices “by the power of the mind” has become a very controversial topic but has also been very well researched in the field of state-of-the-art gadgets, such as smartphones, laptops, tablets and even smart TVs, and also [...] Read more.

In recent years, the control of devices “by the power of the mind” has become a very controversial topic but has also been very well researched in the field of state-of-the-art gadgets, such as smartphones, laptops, tablets and even smart TVs, and also in medicine, to be used by people with disabilities for whom these technologies may be the only way to communicate with the outside world. It is well known that BCI control is a skill and can be improved through practice and training. This paper aims to improve and diversify signal processing methods for the implementation of a brain-computer interface (BCI) based on neurological phenomena recorded during motor tasks using motor imagery (MI). The aim of the research is to extract, select and classify the characteristics of electroencephalogram (EEG) signals, which are based on sensorimotor rhythms, for the implementation of BCI systems. This article investigates systems based on brain-computer interfaces, especially those that use the electroencephalogram as a method of acquisition of MI tasks. The purpose of this article is to allow users to manipulate quadcopter virtual structures (external, robotic objects) simply through brain activity, correlated with certain mental tasks using undecimal transformation (UWT) to reduce noise, Independent Component Analysis (ICA) together with determination coefficient (r²) and, for classification, a hybrid neural network consisting of Radial Basis Functions (RBF) and a multilayer perceptron–recurrent network (MLP–RNN), obtaining a classification accuracy of 95.5%. Following the tests performed, it can be stated that the use of biopotentials in human–computer interfaces is a viable method for applications in the field of BCI. The results presented show that BCI training can produce a rapid change in behavioral performance and cognitive properties. If more than one training session is used, the results may be beneficial for increasing poor cognitive performance. To achieve this goal, three steps were taken: understanding the functioning of BCI systems and the neurological phenomena involved; acquiring EEG signals based on sensorimotor rhythms recorded during MI tasks; applying and optimizing extraction methods, selecting and classifying characteristics using neuronal networks. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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9 pages, 4163 KiB

Open AccessArticle

Development of a Motorized Hospital Bed with Swerve Drive Modules for Holonomic Mobility

by Radon Dhelika, Ali Fajar Hadi and Prasandhya Astagiri Yusuf

Appl. Sci. 2021, 11(23), 11356; https://doi.org/10.3390/app112311356 - 30 Nov 2021

Cited by 4 | Viewed by 4381

Abstract

In hospitals; transferring patients using hospital beds is time consuming and inefficient. Additionally; the task of frequently pushing and pulling beds poses physical injury risks to nurses and caregivers. Motorized hospital beds with holonomic mobility have been previously proposed. However; most such beds [...] Read more.

In hospitals; transferring patients using hospital beds is time consuming and inefficient. Additionally; the task of frequently pushing and pulling beds poses physical injury risks to nurses and caregivers. Motorized hospital beds with holonomic mobility have been previously proposed. However; most such beds come with complex drivetrain which makes them costly and hinders larger-scale adoption in hospitals. In this study; a motorized hospital bed that utilizes a swerve drive mechanism is proposed. The design takes into account simplicity which would allow for minimum modification of the existing beds. Two DC motors for steering and propulsion are used for a single swerve drive module. The control of the propulsion motor is achieved by a combination of trajectory planning based on quintic polynomials and PID control. Further; the control performance of the proposed bed was evaluated; and the holonomic mobility of its prototype was successfully demonstrated. An average error of less than 3% was obtained for motion with a constant velocity; however; larger values in the range of 15% were observed for other conditions, such as accelerating and decelerating. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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16 pages, 2962 KiB

Open AccessArticle

Autonomous Driving Control Using the DDPG and RDPG Algorithms

by Che-Cheng Chang, Jichiang Tsai, Jun-Han Lin and Yee-Ming Ooi

Appl. Sci. 2021, 11(22), 10659; https://doi.org/10.3390/app112210659 - 12 Nov 2021

Cited by 18 | Viewed by 4316

Abstract

Recently, autonomous driving has become one of the most popular topics for smart vehicles. However, traditional control strategies are mostly rule-based, which have poor adaptability to the time-varying traffic conditions. Similarly, they have difficulty coping with unexpected situations that may occur any time [...] Read more.

Recently, autonomous driving has become one of the most popular topics for smart vehicles. However, traditional control strategies are mostly rule-based, which have poor adaptability to the time-varying traffic conditions. Similarly, they have difficulty coping with unexpected situations that may occur any time in the real-world environment. Hence, in this paper, we exploited Deep Reinforcement Learning (DRL) to enhance the quality and safety of autonomous driving control. Based on the road scenes and self-driving simulation modules provided by AirSim, we used the Deep Deterministic Policy Gradient (DDPG) and Recurrent Deterministic Policy Gradient (RDPG) algorithms, combined with the Convolutional Neural Network (CNN), to realize the autonomous driving control of self-driving cars. In particular, by using the real-time images of the road provided by AirSim as the training data, we carefully formulated an appropriate reward-generation method to improve the convergence speed of the adopted DDPG and RDPG models and the control performance of moving driverless cars. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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23 pages, 7155 KiB

Open AccessArticle

A Brief Review on Challenges in Design and Development of Nanorobots for Medical Applications

by Gautham Giri, Yaser Maddahi and Kourosh Zareinia

Appl. Sci. 2021, 11(21), 10385; https://doi.org/10.3390/app112110385 - 5 Nov 2021

Cited by 31 | Viewed by 17891

Abstract

Robotics is a rapidly growing field, and the innovative idea to scale down the size of robots to the nanometer level has paved a new way of treating human health. Nanorobots have become the focus of many researchers aiming to explore their many [...] Read more.

Robotics is a rapidly growing field, and the innovative idea to scale down the size of robots to the nanometer level has paved a new way of treating human health. Nanorobots have become the focus of many researchers aiming to explore their many potential applications in medicine. This paper focuses on manufacturing techniques involved in the fabrication of nanorobots and their associated challenges in terms of design architecture, sensors, actuators, powering, navigation, data transmission, followed by challenges in applications. In addition, an overview of various nanorobotic systems addresses different architectures of a nanorobot. Moreover, multiple medical applications, such as oncology, drug delivery, and surgery, are reviewed and summarized. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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17 pages, 10306 KiB

Open AccessArticle

A Path Planning Strategy for Multi-Robot Moving with Path-Priority Order Based on a Generalized Voronoi Diagram

by Sheng-Kai Huang, Wen-June Wang and Chung-Hsun Sun

Appl. Sci. 2021, 11(20), 9650; https://doi.org/10.3390/app11209650 - 15 Oct 2021

Cited by 30 | Viewed by 3698

Abstract

This paper proposes a new path planning strategy called the navigation strategy with path priority (NSPP) for multiple robots moving in a large flat space. In the space, there may be some static or/and dynamic obstacles. Suppose we have the path-priority order for [...] Read more.

This paper proposes a new path planning strategy called the navigation strategy with path priority (NSPP) for multiple robots moving in a large flat space. In the space, there may be some static or/and dynamic obstacles. Suppose we have the path-priority order for each robot, then this article aims to find an efficient path for each robot from its starting point to its target point without any collision. Here, a generalized Voronoi diagram (GVD) is used to perform the map division based on each robot’s path-priority order, and the proposed NSPP is used to do the path planning for the robots in the space. This NSPP can be applied to any number of robots. At last, there are several simulations with a different number of robots in a circular or rectangular space to be shown that the proposed method can complete the task effectively and has better performance in average trajectory length than those by using the benchmark methods of the shortest distance algorithm (SDA) and reciprocal orientation algorithm (ROA). Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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57 pages, 3098 KiB

Open AccessArticle

Empirical Study of Constraint-Handling Techniques in the Optimal Synthesis of Mechanisms for Rehabilitation

by José Saúl Muñoz-Reina, Miguel Gabriel Villarreal-Cervantes and Leonel Germán Corona-Ramírez

Appl. Sci. 2021, 11(18), 8739; https://doi.org/10.3390/app11188739 - 19 Sep 2021

Cited by 3 | Viewed by 2529

Abstract

Currently, rehabilitation systems with closed kinematic chain mechanisms are low-cost alternatives for treatment and health care. In designing these systems, the dimensional synthesis is commonly stated as a constrained optimization problem to achieve repetitive rehabilitation movements, and metaheuristic algorithms for constrained problems are [...] Read more.

Currently, rehabilitation systems with closed kinematic chain mechanisms are low-cost alternatives for treatment and health care. In designing these systems, the dimensional synthesis is commonly stated as a constrained optimization problem to achieve repetitive rehabilitation movements, and metaheuristic algorithms for constrained problems are promising methods for searching solutions in the complex search space. The Constraint Handling Techniques (CHTs) in metaheuristic algorithms have different capacities to explore and exploit the search space. However, the study of the relationship in the CHT performance of the mechanism dimensional synthesis for rehabilitation systems has not been addressed, resulting in an important gap in the literature of such problems. In this paper, we present a comparative empirical study to investigate the influence of four CHTs (penalty function, feasibility rules, stochastic-ranking, and

ϵ

-constraint) on the performance of ten representative algorithms that have been reported in the literature for solving mechanism synthesis for rehabilitation (four-bar linkage, eight-bar linkage, and cam-linkage mechanisms). The study involves analysis of the overall performance, six performance metrics, and evaluation of the obtained mechanism. This identified that feasibility rules usually led to efficient optimization for most analyzed algorithms and presented more consistency of the obtained results in these kinds of problems. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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16 pages, 28788 KiB

Open AccessArticle

Workspace Analysis of a Mobile Manipulator with Obstacle Avoidance in 3D Printing Tasks

by Robert Guamán Rivera, Rodrigo García Alvarado, Alejandro Martínez-Rocamora and Fernando Auat Cheein

Appl. Sci. 2021, 11(17), 7923; https://doi.org/10.3390/app11177923 - 27 Aug 2021

Cited by 5 | Viewed by 2777

Abstract

The knowledge of the workspace for a robotic system on construction sites represents an essential resource to ensure the work progress, guarantee the safety of the construction tasks, and avoid robot damage. Despite the dramatic development of 3D printing technologies with robotic systems [...] Read more.

The knowledge of the workspace for a robotic system on construction sites represents an essential resource to ensure the work progress, guarantee the safety of the construction tasks, and avoid robot damage. Despite the dramatic development of 3D printing technologies with robotic systems in recent years, these are still several challenges to consider, such as the size of the printing profile and obstacles in the construction site. This work presents the results from evaluating the workspace of a mobile manipulator in 3D printing tasks on construction sites. The methodology analyses the printing workspace based on the workspace of the mobile manipulator, considering fixed obstacles and possible collisions between the robot and obstacles during 3D printing tasks. The results showed that the shape of the printing profile defined as a building element changes the shape of the printing workspace. Furthermore, the obstacles in the construction site and height variation of the printing profile cause changes in the displacement of the robotic platform and values of rotation of its joints, which also modify the shape of the printing workspace. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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19 pages, 2880 KiB

Open AccessArticle

On Unmanned Aerial Vehicles Light Show Systems: Algorithms, Software and Hardware

by Jie Huang, Guoqing Tian, Jiancheng Zhang and Yutao Chen

Appl. Sci. 2021, 11(16), 7687; https://doi.org/10.3390/app11167687 - 21 Aug 2021

Cited by 13 | Viewed by 3456

Abstract

Unmanned aerial vehicle (UAV) light shows (UAV-LS) have a wow factor due to their advantages in terms of environment friendliness and controllability compared to traditional fireworks. In this paper, a UAV-LS system is developed including a collision-free formation transformation trajectory planning algorithm, a [...] Read more.

Unmanned aerial vehicle (UAV) light shows (UAV-LS) have a wow factor due to their advantages in terms of environment friendliness and controllability compared to traditional fireworks. In this paper, a UAV-LS system is developed including a collision-free formation transformation trajectory planning algorithm, a software package that facilitates animation design and real-time monitoring and control, and hardware design and realization. In particular, a dynamic task assignment algorithm based on graph theory is proposed to reduce the impact of UAV collision avoidance on task assignment and the frequency of task assignment in the formation transformation. In addition, the software package consists of an animation interface for formation drawing and 3D animation simulation, which helps the monitoring and control of UAVs through a real-time monitoring application. The developed UAV-LS system hardware consists of subsystems of decision-making, real-time kinematic (RTK) global positioning system (GPS), wireless communication, and UAV platforms. Outdoor experiments using six quadrotors are performed and details of implementations of high-accuracy positioning, communication, and computation are presented. Results show that the developed UAV-LS system can successfully complete a light show and the proposed task assignment algorithm performs better than traditional static ones. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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19 pages, 2917 KiB

Open AccessArticle

Research on Kinematic Parameters of Multiple Gait Pattern Transitions

by Chaoyue Guo, Yali Liu, Qiuzhi Song and Shuting Liu

Appl. Sci. 2021, 11(15), 6911; https://doi.org/10.3390/app11156911 - 27 Jul 2021

Cited by 3 | Viewed by 2055

Abstract

Gait recognition technology is the key technology in the field of exoskeletons. In the current research of gait recognition technology, there is less focus on the recognition of the transition between gait patterns. This study aims to determine which kinematic parameters have significant [...] Read more.

Gait recognition technology is the key technology in the field of exoskeletons. In the current research of gait recognition technology, there is less focus on the recognition of the transition between gait patterns. This study aims to determine which kinematic parameters have significant differences in the transitions (between level and stair walking and between level and ramp walking) of different gait patterns, to determine whether these parameters change differently in different gait pattern transitions, and the order the significant differences occur through a comparative analysis of various kinematic parameters between the transition stride and the before stride in the former pattern. We analyzed 18 parameters concerning both lower limbs and trunk. We compared each time point of the transition strides to the corresponding time points of the before stride using a series of two-sample t-tests, and we then evaluated the difference between the transition stride and the before stride based upon the number of time points within the gait cycle that were statistically different. We found that the sagittal plane angular velocity and the angular acceleration of all joints and the resultant velocity of the thigh and shank of the leading limb had significant differences in the process of transition; the sagittal plane angular velocity of all joints of the trailing limb and the velocity of the trunk in the coronary axis direction also showed a significant difference. The angular acceleration of all joints, the sagittal plane angular velocity of the ankle joint of the leading limb, and the acceleration of the trunk in the coronal axis direction showed a difference in the early stage of the transition. In general, the leading limb had a significant difference earlier than the trailing limb, and the acceleration parameters changed earlier than the velocity parameters. These parameters showed different combinations of changes in the transition of different gait patterns, and the changes in these parameters reflected different gait pattern transitions. Therefore, we believe that the results of this study can provide a reference for the gait pattern transition recognition of wearable exoskeletons. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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16 pages, 2601 KiB

Open AccessArticle

Quantitative Assessment of Motor Function by an End-Effector Upper Limb Rehabilitation Robot Based on Admittance Control

by Chao Qian, Wei Li, Tianyu Jia, Chong Li, Ping-Ju Lin, Yiyong Yang and Linhong Ji

Appl. Sci. 2021, 11(15), 6854; https://doi.org/10.3390/app11156854 - 26 Jul 2021

Cited by 11 | Viewed by 3090

Abstract

Various rehabilitation robots have been developed to assist the movement training of the upper limbs of stroke patients, among which some have been used to evaluate the motor recovery. However, how to understand the recovery of motor function from the quantitative assessment following [...] Read more.

Various rehabilitation robots have been developed to assist the movement training of the upper limbs of stroke patients, among which some have been used to evaluate the motor recovery. However, how to understand the recovery of motor function from the quantitative assessment following robot-assisted rehabilitation training is still not clear. The objective of this study is to propose a quantitative assessment method of motor function based on the force and trajectory characteristics during robotic training to reflect motor functional recovery. To assist stroke patients who are not able to move voluntarily, an assistive training mode was developed for the robot-assisted rehabilitation system based on admittance control. Then, to validate the relationship between characteristic information and functional recovery, a clinical experiment was conducted, in which nine stroke patients and nine healthy subjects were recruited. The results showed a significant difference in movement range and movement smoothness during trajectory tracking tasks between stroke patients and healthy subjects. The two parameters above have a correlation with the Fugl-Meyer Assessment for Upper Extremity (FMU) of the involved patients. The multiple linear regression analysis showed FMU was positively correlated with parameters (

R^{2} = 0.91, p < 0.005

). This finding indicated that the above-mentioned method can achieve quantitative assessment of motor function for stroke patients during robot-assisted rehabilitation training, which can contribute to promoting rehabilitation robots in clinical practice. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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26 pages, 19627 KiB

Open AccessArticle

Design, Modeling, and Control of an Autonomous Legged-Wheeled Hybrid Robotic Vehicle with Non-Rigid Joints

by Vítor H. Pinto, Inês N. Soares, Marco Rocha, José Lima, José Gonçalves and Paulo Costa

Appl. Sci. 2021, 11(13), 6116; https://doi.org/10.3390/app11136116 - 30 Jun 2021

Cited by 9 | Viewed by 3577

Abstract

This paper presents a legged-wheeled hybrid robotic vehicle that uses a combination of rigid and non-rigid joints, allowing it to be more impact-tolerant. The robot has four legs, each one with three degrees of freedom. Each leg has two non-rigid rotational joints with [...] Read more.

This paper presents a legged-wheeled hybrid robotic vehicle that uses a combination of rigid and non-rigid joints, allowing it to be more impact-tolerant. The robot has four legs, each one with three degrees of freedom. Each leg has two non-rigid rotational joints with completely passive components for damping and accumulation of kinetic energy, one rigid rotational joint, and a driving wheel. Each leg uses three independent DC motors—one for each joint, as well as a fourth one for driving the wheel. The four legs have the same position configuration, except for the upper hip joint. The vehicle was designed to be modular, low-cost, and its parts to be interchangeable. Beyond this, the vehicle has multiple operation modes, including a low-power mode. Across this article, the design, modeling, and control stages are presented, as well as the communication strategy. A prototype platform was built to serve as a test bed, which is described throughout the article. The mechanical design and applied hardware for each leg have been improved, and these changes are described. The mechanical and hardware structure of the complete robot is also presented, as well as the software and communication approaches. Moreover, a realistic simulation is introduced, along with the obtained results. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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Rheumatoid Arthritis Diagnosis: Deep Learning vs. Humane

by George P. Avramidis, Maria P. Avramidou and George A. Papakostas

Appl. Sci. 2022, 12(1), 10; https://doi.org/10.3390/app12010010 - 21 Dec 2021

Cited by 11 | Viewed by 8617

Abstract

Rheumatoid arthritis (RA) is a systemic autoimmune disease that preferably affects small joints. As the well-timed diagnosis of the disease is essential for the treatment of the patient, several works have been conducted in the field of deep learning to develop fast and [...] Read more.

Rheumatoid arthritis (RA) is a systemic autoimmune disease that preferably affects small joints. As the well-timed diagnosis of the disease is essential for the treatment of the patient, several works have been conducted in the field of deep learning to develop fast and accurate automatic methods for RA diagnosis. These works mainly focus on medical images as they use X-ray and ultrasound images as input for their models. In this study, we review the conducted works and compare the methods that use deep learning with the procedure that is commonly followed by a medical doctor for the RA diagnosis. The results show that 93% of the works use only image modalities as input for the models as distinct from the medical procedure where more patient medical data are taken into account. Moreover, only 15% of the works use direct explainability methods, meaning that the efforts for solving the trustworthiness issue of deep learning models were limited. In this context, this work reveals the gap between the deep learning approaches and the medical doctors’ practices traditionally applied and brings to light the weaknesses of the current deep learning technology to be integrated into a trustworthy context inside the existed medical infrastructures. Full article

(This article belongs to the Special Issue New Trends in Robotics, Automation and Mechatronics (RAM))

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