Robotics, Volume 10, Issue 4 (December 2021) – 26 articles

Tracking patient progress through a course of robotic tele-rehabilitation requires constant position data logging and comparison, alongside periodic testing with no powered assistance. The test data must be compared with previous test attempts and an ideal baseline, for which a good understanding of the dynamics of the robot is required. The traditional dynamic modelling techniques for serial chain robotics, which involve forming and solving equations of motion, do not adequately describe the multi-domain phenomena that affect the movement of the rehabilitation robot. In this study, a multi-domain dynamic model for an upper limb rehabilitation robot is described. The model, built using a combination of MATLAB, SimScape, and SimScape Multibody, comprises the mechanical electro-mechanical and control domains. The performance of the model was validated against the performance of the robot when unloaded and when loaded with a human arm proxy. It is shown that this combination of software is appropriate for building a dynamic model of the robot and provides advantages over the traditional modelling approach. It is demonstrated that the responses of the model match the responses of the robot with acceptable accuracy, though the inability to model backlash was a limitation. Full article

Omnidirectional planar robots are common these days due to their high mobility, for example in human–robot interactions. The motion of such mechanisms is based on specially designed wheels, which may vary when different terrains are considered. The usage of actuated caster wheels (ACW) may enable the usage of regular wheels. Yet, it is known that an ACW robot with three actuated wheels needs to overcome kinematic singularities. This paper introduces the kinematic model for an ACW omni robot. We present a novel method to overcome the kinematic singularities of the mechanism’s Jacobian matrix by performing the time propagation in the mechanism’s configuration space. We show how the implementation of this method enables the estimation of caster wheels’ swivel angles by tracking the plate’s velocity. We present the mechanism’s kinematics and trajectory tracking in real-world experimentation using a novel robot design. Full article

Several industrial robotic applications that require high speed or high stiffness-to-inertia ratios use parallel kinematic robots. In the cases where the critical point of the application is the speed, the compliance of the main mechanical transmissions placed between the actuators and the parallel kinematic structure can be significantly higher than that of the parallel kinematic structure itself. This paper deals with this kind of system, where the overall performance depends on the maximum speed and on the dynamic behavior. Our research proposes a new approach for the investigation of the modes of vibration of the end-effector placed on the robot structure for a system where the transmission’s compliance is not negligible in relation to the flexibility of the parallel kinematic structure. The approach considers the kinematic and dynamic coupling due to the parallel kinematic structure, the system’s mass distribution and the transmission’s stiffness. In the literature, several papers deal with the dynamic vibration analysis of parallel robots. Some of these also consider the transmissions between the motors and the actuated joints. However, these works mainly deal with the modal analysis of the robot’s mechanical structure or the displacement analysis of the transmission’s effects on the positioning error of the end-effector. The discussion of the proposed approach takes into consideration a linear delta robot. The results show that the system’s natural frequencies and the directions of the end-effector’s modal displacements strongly depend on its position in the working space. Full article

Recently, several deep-learning based navigation methods have been achieved because of a high quality dataset collected from high-quality simulated environments. However, the cost of creating high-quality simulated environments is high. In this paper, we present a concept of the reduced simulation, which can serve as a simplified version of a simulated environment yet be efficient enough for training deep-learning based UAV collision avoidance approaches. Our approach deals with the reality gap between a reduced simulation dataset and real world dataset and can provide a clear guideline for reduced simulation design. Our experimental result confirmed that the reduction in visual features provided by textures and lighting does not affect operating performance with the user study. Moreover, by conducting collision detection experiments, we verified that our reduced simulation outperforms the conventional cost-effective simulations in adaptation capability with respect to realistic simulation and real-world scenario. Full article

The leap motion controller is a commercial low-cost marker-less optical sensor that can track the motion of a human hand by recording various parameters. Upper limb rehabilitation therapy is the treatment of people having upper limb impairments, whose recovery is achieved through continuous motion exercises. However, the repetitive nature of these exercises can be interpreted as boring or discouraging while patient motivation plays a key role in their recovery. Thus, serious games have been widely used in therapies for motivating patients and making the therapeutic process more enjoyable. This paper explores the feasibility, accuracy, and repeatability of a leap motion controller (LMC) to be applied in combination with a serious game for upper limb rehabilitation. Experimental feasibility tests are carried out by using an industrial robot that replicates the upper limb motions and is tracked by using an LMC. The results suggest a satisfactory performance in terms of tracking accuracy although some limitations are identified and discussed in terms of measurable workspace. Full article

The application of force in surgical settings is typically accomplished via physical tethers to the surgical tool. While physical tethers are common and critical, some internal surgical procedures may benefit from a tetherless operation of needles, possibly reducing the number of ports in the patient or the amount of tissue damage caused by tools used to manipulate needles. Magnetic field gradients can dynamically apply kinetic forces to magnetizable objects free of such tethers, possibly enabling ultra-minimally invasive robotic surgical procedures. We demonstrate the untethered manipulation of a suture needle in vitro, exemplified by steering through narrow holes, as well as needle penetration through excised rat and human tissues. We present proof of principle manipulations for the fully untethered control of a minimally modified, standard stainless steel surgical suture needle. Full article

Robotics is an interdisciplinary field and there exist several well-known approaches to represent the dynamics model of a robot arm. The robot arm is an open kinematic chain of links connected through rotational and translational joints. In the general case, it is very difficult to obtain explicit expressions for the forces and the torques in the equations where the driving torques of the actuators produce desired motion of the gripper. The robot arm control depends significantly on the accuracy of the dynamic model. In the existing literature, the complexity of the dynamic model is reduced by linearization techniques or techniques like machine learning for the identification of unmodelled dynamics. This paper proposes a novel approach for deriving the equations of motion and the actuator torques of a robot arm with an arbitrary number of joints. The proposed approach for obtaining the dynamic model in closed form employs graph theory and the orthogonality principle, a powerful concept that serves as a generalization for the law of conservation of energy. The application of this approach is demonstrated using a 3D-printed planar robot arm with three degrees of freedom. Computer experiments for this robot are executed to validate the dynamic characteristics of the mathematical model of motion obtained by the application of the proposed approach. The results from the experiments are visualized and discussed in detail. Full article

This work is aimed to demonstrate a multi-objective joint trajectory generation algorithm for a 7 degree of freedom (DoF) robotic manipulator using swarm intelligence (SI)—product of exponentials (PoE) combination. Given a priori knowledge of the end-effector Cartesian trajectory and obstacles in the workspace, the inverse kinematics problem is tackled by SI-PoE subject to multiple constraints. The algorithm is designed to satisfy finite jerk constraint on end-effector, avoid obstacles, and minimize control effort while tracking the Cartesian trajectory. The SI-PoE algorithm is compared with conventional inverse kinematics algorithms and standard particle swarm optimization (PSO). The joint trajectories produced by SI-PoE are experimentally tested on Sawyer 7 DoF robotic arm, and the resulting torque trajectories are compared. Full article

This paper describes the development and experimental validation of algorithms for a novel laser vision system (LVS), suitable for measuring the relative posture from both solid and mesh-like targets in underwater environments. The system was developed in the framework of the AQUABOT project, a research project dedicated to the development of an underwater robotic system for inspection of offshore aquaculture installations. In particular, an analytical model for three-medium refraction that takes into account the nonlinear hemispherical optics for image rectification has been developed. The analytical nature of the model allows the online estimation of the refractive index of the external medium. The proposed LVS consists of three line-lasers within the field of view of the underwater robot camera. The algorithms that have been developed in this work provide appropriately filtered point-cloud datasets from each laser, as well as high-level information such as distance and relative orientation of the target with respect to the ROV. In addition, an automatic calibration procedure, along with the accompanying hardware for the underwater laser vision system has been developed to reduce the calibration overhead required by regular maintenance operations for underwater robots operating in seawater. Furthermore, a spatial image filter was developed for discriminating between mesh and non-mesh-like targets in the LVS measurements. Finally, a set of experiments was carried out in a controlled laboratory environment, as well as in real conditions at offshore aquaculture installations demonstrating the performance of the system. Full article

Autonomous robots are playing an important role to solve the Simultaneous Localization and Mapping (SLAM) problem in different domains. To generate flexible, intelligent, and interoperable solutions for SLAM, it is a must to model the complex knowledge managed in these scenarios (i.e., robots characteristics and capabilities, maps information, locations of robots and landmarks, etc.) with a standard and formal representation. Some studies have proposed ontologies as the standard representation of such knowledge; however, most of them only cover partial aspects of the information managed by SLAM solutions. In this context, the main contribution of this work is a complete ontology, called OntoSLAM, to model all aspects related to autonomous robots and the SLAM problem, towards the standardization needed in robotics, which is not reached until now with the existing SLAM ontologies. A comparative evaluation of OntoSLAM with state-of-the-art SLAM ontologies is performed, to show how OntoSLAM covers the gaps of the existing SLAM knowledge representation models. Results show the superiority of OntoSLAM at the Domain Knowledge level and similarities with other ontologies at Lexical and Structural levels. Additionally, OntoSLAM is integrated into the Robot Operating System (ROS) and Gazebo simulator to test it with Pepper robots and demonstrate its suitability, applicability, and flexibility. Experiments show how OntoSLAM provides semantic benefits to autonomous robots, such as the capability of inferring data from organized knowledge representation, without compromising the information for the application and becoming closer to the standardization needed in robotics. Full article

In this work, we present methods allowing parallel, hybrid, and serial manipulators to be analyzed, calibrated, and controlled with the same analytical tools. We introduce a general approach to describe any robotic manipulator using established serial-link representations. We use this framework to generate analytical kinematic and calibration Jacobians for general manipulator constructions using null space constraints and extend the methods to hybrid manipulator types with complex geometry. We leverage the analytical Jacobians to develop detailed expressions for post-calibration pose uncertainties that are applied to describe the relationship between data set size and post-calibration uncertainty. We demonstrate the calibration of a hybrid manipulator assembled from high precision calibrated industrial components resulting in 91.1 $\mathsf{\mu }$m RMS position error and 71.2 $\mathsf{\mu }$rad RMS rotation error, representing a 46.7% reduction compared to the baseline calibration of assembly offsets. Full article

Safe operation, energy efficiency, versatility and kinematic compatibility are the most important aspects in the design of rehabilitation exoskeletons. This paper focuses on the conceptual bio-inspired mechanical design and equilibrium point control (EP) of a new human upper limb exoskeleton. Considering the upper limb as a multi-muscle redundant system, a similar over-actuated but cable-driven mechatronic system is developed to imitate upper limb motor functions. Additional torque adjusting systems at the joints allow users to lift light weights necessary for activities of daily living (ADL) without increasing electric motor powers of the device. A theoretical model of the “ideal” artificial muscle exoskeleton is also developed using Hill’s natural muscle model. Optimal design parameters of the exoskeleton are defined using the differential evolution (DE) method as a technique of a multi-objective optimization. The proposed cable-driven exoskeleton was then fabricated and tested on a healthy subject. Results showed that the proposed system fulfils the desired aim properly, so that it can be utilized in the design of rehabilitation robots. Further studies may include a spatial mechanism design, which is especially important for the shoulder rehabilitation, and development of reinforcement learning control algorithms to provide more efficient rehabilitation treatment. Full article

In this paper, we study the “Multi-Robot Routing problem” with min–max objective (MRR-MM) in detail. It involves the assignment of sequentially ordered tasks to robots such that the maximum cost of the slowest robot is minimized. The problem description, the different types of formulations, and the methods used across various research communities are discussed in this paper. We propose a new problem formulation by treating this problem as a permutation matrix. A comparative study is done between three methods: Stochastic simulated annealing, deterministic mean-field annealing, and a heuristic-based graph search method. Each method is investigated in detail with several data sets (simulation and real-world), and the results are analysed and compared with respect to scalability, computational complexity, optimality, and its application to real-world scenarios. The paper shows that the heuristic method produces results very quickly with good scalability. However, the solution quality is sub-optimal. On the other hand, when optimal or near-optimal results are required with considerable computational resources, the simulated annealing method proves to be more efficient. However, the results show that the optimal choice of algorithm depends on the dataset size and the available computational budget. The contribution of the paper is three-fold: We study the MRR-MM problem in detail across various research communities. This study also shows the lack of inter-research terminology that has led to different names for the same problem. Secondly, formulating the task allocation problem as a permutation matrix formulation has opened up new approaches to solve this problem. Thirdly, we applied our problem formulation to three different methods and conducted a detailed comparative study using real-world and simulation data. Full article

The increasing presence of additive manufacturing (AM) in the space sector prompted us to investigate the feasibility of a single degree of freedom (DoF) pointing system (PS) made by means of a compound planetary gear train system (C-PGTS) integrating a dynamic balancing system (DBS) and entirely realized in AM. We analyzed in detail the dynamics of the system dealing with the design and the realization of the prototype. Of fundamental importance for this paper is the careful selection of materials for AM suitable for the prohibitive conditions of space. The results, deriving from the comparison between the experimental part and the simulations, underline the correct dimensioning of the PS and the fundamental importance of DBS in maintaining the satellite attitude. The results also confirm the capabilities of AM in the production of complex mechanical systems, allowing high precision, combined with interesting mechanical properties and low weight.This suggests the potential of AM in the space domain, both for structural parts and active components, such as those listed in this work. Full article

Personalization and localization are important when developing social robots for different sectors, including education, industry, healthcare or restaurants. This allows for an adjustment of robot behaviors according to the needs, preferences or personality of an individual when referring to personalization or to the social conventions or the culture of a country when referring to localization. However, there are different models that enable personalization and localization presented in the current literature, each with their advantages and drawbacks. This work aims to help researchers in the field of social robotics by reviewing and analyzing different papers in this domain. We specifically focus our review by exploring different robots that employ distinct models for the adaptation of the robot to its environment. Additionally, we study an array of methods used to adapt the nonverbal and verbal skills of social robots, including state-of-the-art techniques in artificial intelligence. Full article

A novel, semi-autonomous radiological scanning system for inspecting irregularly shaped and radiologically uncharacterised objects in various orientations is presented. The system utilises relatively low cost, commercial-off-the-shelf (COTS) electronic components, and is intended for use within relatively low to medium radioactive dose environments. To illustrate the generic concepts, the combination of a low-cost COTS vision system, a six DoF manipulator and a gamma radiation spectrometer are investigated. Three modes of vision have been developed, allowing a remote operator to choose the most appropriate algorithm for the task. The robot arm subsequently scans autonomously across the selected object, determines the scan positions and enables the generation of radiological spectra using the gamma spectrometer. These data inform the operator of any likely radioisotopes present, where in the object they are located and thus whether the object should be treated as LLW, ILW or HLW. Full article

Nowadays, origami folding in combination with actuation mechanisms can offer deployable structure design, yield compliance, and have several properties of soft material. An easy complex folding pattern can yield an array of functionalities in actuated hinges or active spring elements. This paper presents various cylinder origami robot designs that can be untethered magnetically actuated. The different designs are analyzed and compared to achieve the following three types of motion: Peristaltic, rolling, and turning in different environments, namely, board, sandpaper, and sand. The proposed origami robot is able translate 53 mm in peristaltic motion within 20 s and is able to roll one complete cycle in 1 s and can turn ≈180${}^{\circ }$ in 1.5 s. The robot also demonstrated a peristaltic locomotion at a speed of ≈2.5 mm s${}^{-1}$, ≈1.9 mm s${}^{-1}$, and ≈1.3 mm s${}^{-1}$ in board, sandpaper, and sand respectively; rolling motion at a speed of 1 cycle s${}^{-1}$, ≈0.66 cycles s${}^{-1}$, and ≈0.33 cycles s${}^{-1}$ in board, sandpaper, and sand respectively; and turning motion of ≈180${}^{\circ }$, ≈83${}^{\circ }$, and ≈58${}^{\circ }$ in board, sandpaper, and sand respectively. The evaluation of the robotic motion and actuation is discussed in detail in this paper. Full article

In this study, a novel design for a compact, lightweight, agile, omnidirectional three-legged robot involving legs with four degrees of freedom, utilizing an spherical parallel mechanism with an additional non-redundant central support joint for the robot hip structure is proposed. The general design and conceptual ideas for the robot are presented, targeting a close match of the well-known SLIP-model. CAD models, 3d-printed prototypes, and proof-of-concept multi-body simulations are shown, investigating the feasibility to employ a geometrically dense spherical parallel manipulator with completely spherically shaped shell-type parts for the highly force-loaded application in the legged robot hip mechanism. Furthermore, in this study, an analytic expression is derived, yielding the calculation of stress forces acting inside the linkage structures, by directly constructing the manipulator hip Jacobian inside the force domain. Full article

In this paper, we present a mixed-initiative motion control strategy for multiple quadrotor aerial vehicles. The proposed approach incorporates formation specifications and motion-planning commands as well as inputs by a human operator. More specifically, we consider a leader–follower aerial robotic system, which autonomously attains a specific geometrical formation, by regulating the distances among neighboring agents while avoiding inter-robot collisions. The desired formation is realized by a decentralized prescribed performance control strategy, resulting in a low computational complexity implementation with guaranteed robustness and accurate formation establishment. The multi-robot system is safely guided towards goal configurations, by employing a properly defined navigation function that provides appropriate motion commands to the leading vehicle, which is the only one that has knowledge of the workspace and the goal configurations. Additionally, the overall framework incorporates human commands that dictate the motion of the leader via a teleoperation interface. The resulting mixed-initiative control system has analytically guaranteed stability and convergence properties. A realistic simulation study, considering a team of five quadrotors operating in a cluttered environment, was carried out to demonstrate the performance of the proposed strategy. Full article

This paper presents an inverse kinematic controller using neural networks for trajectory controlling of a delta robot in real-time. The developed control scheme is purely data-driven and does not require prior knowledge of the delta robot kinematics. Moreover, it can adapt to the changes in the kinematics of the robot. For developing the controller, the kinematic model of the delta robot is estimated by using neural networks. Then, the trained neural networks are configured as a controller in the system. The parameters of the neural networks are updated while the robot follows a path to adaptively compensate for modeling uncertainties and external disturbances of the control system. One of the main contributions of this paper is to show that updating the parameters of neural networks offers a smaller tracking error in inverse kinematic control of a delta robot with consideration of joint backlash. Different simulations and experiments are conducted to verify the proposed controller. The results show that in the presence of external disturbance, the error in trajectory tracking is bounded, and the negative effect of joint backlash in trajectory tracking is reduced. The developed method provides a new approach to the inverse kinematic control of a delta robot. Full article

This paper presents the design, modeling, analysis, and experimental results of a novel bipedal robotic system that utilizes two interconnected single degree-of-freedom (DOF) leg mechanisms to produce stable forward locomotion and steering. The single DOF leg is actuated via a Reuleaux triangle cam-follower mechanism to produce a constant body height foot trajectory. Kinematic analysis and dimension selection of the Reuleaux triangle mechanism is conducted first to generate the desired step height and step length. Leg sequencing is then designed to allow the robot to maintain a constant body height and forward walking velocity. Dynamic simulations and experiments are conducted to evaluate the walking and steering performance. The results show that the robot is able to control its body orientation, maintain a constant body height, and achieve quasi-static locomotion stability. Full article

Catching flying objects is a challenging task in human–robot interaction. Traditional techniques predict the intersection position and time using the information obtained during the free-flying ball motion. A common pain point in these systems is the short ball flight time and uncertainties in the ball’s trajectory estimation. In this paper, we present the Robot Anticipation Learning System (RALS) that accounts for the information obtained from observation of the thrower’s hand motion before the ball is released. RALS takes extra time for the robot to start moving in the direction of the target before the opponent finishes throwing. To the best of our knowledge, this is the first robot control system for ball-catching with anticipation skills. Our results show that the information fused from both throwing and flying motions improves the ball-catching rate by up to 20% compared to the baseline approach, with the predictions relying only on the information acquired during the flight phase. Full article

Dealing safely with nuclear waste is an imperative for the nuclear industry. Increasingly, robots are being developed to carry out complex tasks such as perceiving, grasping, cutting, and manipulating waste. Radioactive material can be sorted, and either stored safely or disposed of appropriately, entirely through the actions of remotely controlled robots. Radiological characterisation is also critical during the decommissioning of nuclear facilities. It involves the detection and labelling of radiation levels, waste materials, and contaminants, as well as determining other related parameters (e.g., thermal and chemical), with the data visualised as 3D scene models. This paper overviews work by researchers at the QMUL Centre for Advanced Robotics (ARQ), a partner in the UK EPSRC National Centre for Nuclear Robotics (NCNR), a consortium working on the development of radiation-hardened robots fit to handle nuclear waste. Three areas of nuclear-related research are covered here: human–robot interfaces for remote operations, sensor delivery, and intelligent robotic manipulation. Full article

Currently, a large number of investigations are being carried out in the area of robotics focused on proposing solutions in the field of health, and many of them have directed their efforts on issues related to the health emergency due to COVID-19. Considering that one of the ways to reduce the risk of contagion is by avoiding contact and closeness between people when exchanging supplies such as food, medicine, clothing, etc., this work proposes the use of a planar cable-driven parallel robot for the transport of supplies in hospitals whose room distribution has planar architecture. The robot acts in accordance with a procedure proposed for each task to be carried out, which includes the process of disinfection (based on Ultraviolet-C light) of the supplies transported inside the robot’s end effector. The study presents a design proposal for the geometry of the planar cable-driven parallel robots and its end effector, as well as the software simulations that allow evaluating the robot’s movement trajectories and the responses of the position control system based on Fuzzy-PID controllers. Full article

Grocery shoppers must negotiate cluttered, crowded, and complex store layouts containing a vast variety of products to make their intended purchases. This complexity may prevent even experienced shoppers from finding their grocery items, consuming a lot of their time and resulting in monetary loss for the store. To address these issues, we present a generic grocery robot architecture for the autonomous search and localization of products in crowded dynamic unknown grocery store environments using a unique context Simultaneous Localization and Mapping (contextSLAM) method. The contextSLAM method uniquely creates contextually rich maps through the online fusion of optical character recognition and occupancy grid information to locate products and aid in robot localization in an environment. The novelty of our robot architecture is in its ability to intelligently use geometric and contextual information within the context map to direct robot exploration in order to localize products in unknown environments in the presence of dynamic people. Extensive experiments were conducted with a mobile robot to validate the overall architecture and contextSLAM, including in a real grocery store. The results of the experiments showed that our architecture was capable of searching for and localizing all products in various grocery lists in different unknown environments. Full article

Developing a dexterous robotic hand that mimics natural human hand movements is challenging due to complicated hand anatomy. Such a practical design should address several requirements, which are often conflicting and force the designer to prioritize the main design characteristics for a given application. Therefore, in the existing designs the requirements are only partially satisfied, leading to complicated and bulky solutions. To address this gap, a novel single-actuated, cable-driven, and self-contained robotic hand is presented in this work. This five-fingered robotic hand supports 19 degrees of freedom (DOFs) and can perform a wide range of precision and power grasps. The external structure of fingers and the thumb is inspired by Pisa/IIT SoftHand, while major modifications are implemented to significantly decrease the number of parts and the effect of friction. The cable configuration is inspired by the tendon structure of the hand anatomy. Furthermore, a novel power transmission system is presented in this work. This mechanism addresses compactness and underactuation, while ensuring proper force distribution through the fingers and the thumb. Moreover, this power transmission system can achieve adaptive grasps of objects with unknown geometries, which significantly simplifies the sensory and control systems. A 3D-printed prototype of the proposed design is fabricated and its base functionality is evaluated through simulations and experiments. Full article