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Electronics
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Path Planning and Control for Robotics
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Path Planning and Control for Robotics

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Systems & Control Engineering".

Deadline for manuscript submissions: closed (15 July 2023) | Viewed by 8102

Special Issue Editors

Dr. Zhou Zhang

E-Mail Website
Guest Editor
Department of Mechanical Engineering Technology, New York City College of Technology, New York, NY 11201, USA
Interests: mechatronics; robotics and control; virtual reality; computer vision; embedded system design; mechanical system design
Dr. Yizhe Chang

E-Mail Website
Guest Editor
Department of Mechanical Engineering, California State Polytechnic University, Pomona, CA 91768, USA
Interests: robotics; human-robot interaction; mechatronics; virtual environment; engineering education
Dr. Allahyar Montazeri

E-Mail Website
Guest Editor
Department of Engineering, Lancaster University, Lancaster LA1 4YW, UK
Interests: adaptive control and signal processing; nonlinear robust control; linear and nonlinear system identification; estimation theory and evolutionary computing and optimization with applications in robotics and autonomous systems as well as active noise and vibration control systems

Special Issue Information

Dear Colleagues,

Although robot path planning and control research started as early as late 1960s, the popularity and progress speed in these fields are increasing. The path planning might be implemented in both the structured and unstructured environments via intensive computation with hardware, software, and algorithms. The algorithm design requires integration of kinematic and dynamic of the mobile robots or manipulators while considering other constraints imposed by the environment.

Although the publications relating to the path planning and control are ubiquitous, there is an ever increasing interest in areas such as industrial automation, unmanned aerial and ground systems, nano locomotion, agriculture automation, virtual rehabilitation, rescue robots, prosthesis, medical surgery, etc. which in turn intensify the use of the path planning into advanced robotics. Hitherto, the researchers are confronting the challenges by integrating many cutting-edge techniques that involve wireless sensor & actuator networks, parallel computing, the internet of things, artificial intelligence, computer vision, and other novel research approaches.

To promote the innovation in robot path planning and control methodologies, this special issue is to solicit but not limit the following topics:

  • Object recognition to promote cognitive robotics in path planning
  • Human motion synthesis to develop the bionic robot
  • Wireless sensor and actuator network used in path planning and control of robots
  • Path planning for automation of surgery robot
  • Nonholonomic system to mobile robotics
  • Collision detection and path-planning in structured or unstructured environments
  • Computational structure to support path planning and control
  • Trajectory tracking and path planning
  • Collaborative robot and robot motion-control
  • Controllability of mobile robots for path planning
  • Steering methods and topological optimization
  • Supervised and unsupervised learning for environment survey and path planning

Dr. Zhou Zhang
Dr. Yizhe Chang
Dr. Allahyar Montazeri
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • motion planning
  • trajectory generation
  • manipulators
  • mobile robots
  • collision avoidance
  • object recognition
  • collaborative robots

Published Papers (4 papers)

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Research

18 pages, 1861 KiB  
Article
Adaptive Control of Unmanned Aerial Vehicles with Varying Payload and Full Parametric Uncertainties
by Imil Hamda Imran, Kieran Wood and Allahyar Montazeri
Electronics 2024, 13(2), 347; https://doi.org/10.3390/electronics13020347 - 14 Jan 2024
Cited by 2 | Viewed by 772
Abstract
This article investigates an adaptive tracking control problem for a six degrees of freedom (6-DOF) nonlinear quadrotor unmanned aerial vehicle (UAV) with a variable payload mass. The changing payload introduces time-varying parametric uncertainties into the dynamical model, rendering a static control strategy no [...] Read more.
This article investigates an adaptive tracking control problem for a six degrees of freedom (6-DOF) nonlinear quadrotor unmanned aerial vehicle (UAV) with a variable payload mass. The changing payload introduces time-varying parametric uncertainties into the dynamical model, rendering a static control strategy no longer effective. To handle this issue, two adaptive schemes are developed to maintain the uncertainties in the translational and rotational dynamics. Initially, a virtual proportional derivative (PD) is designed to stabilize the horizontal position; however, due to an unknown and time-varying mass, an adaptive controller is proposed to generate the total thrust of the UAV. Furthermore, an adaptive controller is designed for the rotational dynamics, to handle parametric uncertainties, such as inertia and external disturbance parameters. In both schemes, a standard adaptive scheme using the certainty equivalence principle is extended and designed. A stability analysis was conducted with rigorous analytical proofs to show the performance of our proposed controllers, and simulations were implemented to assess the performance against other existing methods. Tracking fitness and total control efforts were calculated and compared with closed-loop adaptive tracking control (CLATC) and adaptive sliding mode control (ASMC). The results indicated that the proposed design better maintained UAV stability. Full article
(This article belongs to the Special Issue Path Planning and Control for Robotics)
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23 pages, 8548 KiB  
Article
Optimal Trajectory Planning for Manipulators with Efficiency and Smoothness Constraint
by Zequan Xu, Wei Wang, Yixiang Chi, Kun Li and Leiying He
Electronics 2023, 12(13), 2928; https://doi.org/10.3390/electronics12132928 - 3 Jul 2023
Cited by 3 | Viewed by 1647
Abstract
Path planning to generate an appropriate time sequence of positions for a complex trajectory is an open challenge in robotics. This paper proposes an optimization method with the integration of an improved ant colony algorithm and a high-order spline interpolation technique. The optimization [...] Read more.
Path planning to generate an appropriate time sequence of positions for a complex trajectory is an open challenge in robotics. This paper proposes an optimization method with the integration of an improved ant colony algorithm and a high-order spline interpolation technique. The optimization process can be modelled as the travelling salesman problem. The greatest features of this method include: (1) automatic generation for complex trajectory and a new idea of selecting the nearest start point instead of using the traditional way of human operation; (2) an optimized motion sequence of the manipulator with the shortest length of the free-load path improves efficiency by nearly 65% and (3) trajectories both in Cartesian space and joint space are interpolated with good smoothness to reduce shocks and vibrations. Simulations and experiments are conducted to demonstrate the good properties of this method. Full article
(This article belongs to the Special Issue Path Planning and Control for Robotics)
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15 pages, 6530 KiB  
Article
Path Planning of Mecanum Wheel Chassis Based on Improved A* Algorithm
by Huimin Xu, Gaohong Yu, Yimiao Wang, Xiong Zhao, Yijin Chen and Jiangang Liu
Electronics 2023, 12(8), 1754; https://doi.org/10.3390/electronics12081754 - 7 Apr 2023
Cited by 5 | Viewed by 2116
Abstract
This study is concerned with path planning in a structured greenhouse, in contrast to much of the previous research addressing applications in outdoor fields. The prototype mainly comprises an independently driven Mecanum wheel, a lidar measuring module, a single-chip microcomputer control board, and [...] Read more.
This study is concerned with path planning in a structured greenhouse, in contrast to much of the previous research addressing applications in outdoor fields. The prototype mainly comprises an independently driven Mecanum wheel, a lidar measuring module, a single-chip microcomputer control board, and a laptop computer. Environmental information collection and mapping were completed on the basis of lidar and laptop computer connection. The path planning algorithm used in this paper expanded the 8-search-neighborhood of the traditional A* algorithm to a 48-search-neighborhood, increasing the search direction and improving the efficiency of path planning. The Floyd algorithm was integrated to smooth the planned path and reduced the turning points in the path. In this way, the problems of the traditional A* algorithm could be solved (i.e., slow the path planning speed and high numbers of redundant points). Tests showed that the turning points, planning path time, and distance of the improved algorithm were the lowest. Compared with the traditional 8-search-neighborhood A* algorithm, the turning point was reduced by 50%, the planning time was reduced by 13.53%, and the planning distance was reduced by 13.96%. Therefore, the improved method of the A* algorithm proposed in this paper improves the precision of the planning path and reduces the planning time, providing a theoretical basis for the navigation, inspection, and standardization construction of greenhouses in the future. Full article
(This article belongs to the Special Issue Path Planning and Control for Robotics)
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34 pages, 11330 KiB  
Article
Modeling, Trajectory Analysis and Waypoint Guidance System of a Biomimetic Underwater Vehicle Based on the Flapping Performance of Its Propulsion System
by Juan Antonio Algarín-Pinto, Luis E. Garza-Castañón, Adriana Vargas-Martínez and Luis I. Minchala-Ávila
Electronics 2022, 11(4), 544; https://doi.org/10.3390/electronics11040544 - 11 Feb 2022
Cited by 2 | Viewed by 2094
Abstract
The performance of biomimetic underwater vehicles directly depends on the correct design of their propulsion system and its control. These vehicles can attain highly efficient motion, hovering and thrust by properly moving part(s) of their bodies. In this article, a mathematical modeling and [...] Read more.
The performance of biomimetic underwater vehicles directly depends on the correct design of their propulsion system and its control. These vehicles can attain highly efficient motion, hovering and thrust by properly moving part(s) of their bodies. In this article, a mathematical modeling and waypoint guidance system for a biomimetic autonomous underwater vehicle (BAUV) is proposed. The BAUV achieves sideways and dorsoventral thunniform motion by flapping its caudal fin through a parallel mechanism. Also, an analysis of the vehicle’s design is presented. A thrust analysis was performed based on the novel propulsion system. Furthermore, the vehicle’s kinematics and dynamic models were derived, where hydrodynamic equations were obtained as well. Computed models were validated using simulations where thrust and moment analysis was employed to visualize the vehicle’s performance while swimming. For the path tracking scheme, a waypoint guidance system was designed to correct the vehicle’s direction toward several positions in space. To accurately obtain waypoints, correction over the propeller’s flapping frequency and bias was employed to achieve proper thrust and orientation of the vehicle. The results from numerical simulations showed how by incorporating this novel propulsion strategy, the BAUV improved its performance when diving and maneuvering based on the dorsoventral and/or sideways configuration of its swimming mode. Furthermore, by designing proper strategies to regulate the flapping performance of its caudal fin, the BAUV followed the desired trajectories. The efficiency for the designed strategy was obtained by comparing the vehicle’s traveled distance and ideal scenarios of straight-line trajectories between targets. During simulations, the designed guidance system presented an efficiency of above 80% for navigation tasks. Full article
(This article belongs to the Special Issue Path Planning and Control for Robotics)
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