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Electronics
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Path Planning for Mobile Robots, 2nd Edition
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Path Planning for Mobile Robots, 2nd Edition

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

Deadline for manuscript submissions: closed (15 October 2024) | Viewed by 6616

Special Issue Editors

Dr. Ionica Oncioiu

E-Mail Website
Guest Editor
Department of Informatics, Faculty of Informatics, Titu Maiorescu University, 040051 Bucharest, Romania
Interests: robotics; autonomous robot; mobility; planning; continuous execution; programming; integrated solution
Special Issues, Collections and Topics in MDPI journals
Dr. Lucian Ştefǎniţǎ Grigore

E-Mail Website
Guest Editor
Center of Excellence in Robotics and Autonomous Systems – CERAS, Military Technical Academy Ferdinand I, 050141 Bucharest, Romania
Interests: robotics; automatic; mechanics; mobile robotics; locomotion; multi body systems; hardware

Special Issue Information

Dear Colleagues,

The development of mobile robots and land vehicles towards autonomy is a very significant area of concern for researchers and engineers in multidisciplinary fields. This growing interest in increasing the quantity of these robots and vehicles, as well as the number of manufacturers involved, necessitates the development of applications for road recognition. These programs aim to create uniform structures that both users and manufacturers can easily adopt, regardless of their individual needs or preferences. The primary reason for the development of applications is the necessity to prevent collisions and facilitate collaboration between mobile robots and land vehicles in various scenarios. There is a growing discussion surrounding the fourth industrial revolution, known as Industry 4.0. This revolution emphasizes the importance of logistical approaches in human–robot interaction systems, focusing on the ability of mobile robots to identify and plan routes effectively.

This Special Issue invites researchers to contribute both with original research articles and reviews highlighting issues related to mobile robot path planning and the challenges of mobile robot path planning applications. At the same time, it can provide solutions to improve planning methods, so that mobile robots can move in structured and unstructured environments.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following: 

  • Connected robot navigation through wireless sensors;
  • Algorithms aimed at achieving dynamic planning, control, and state estimation are optimized for maximum efficiency and effectiveness;
  • Robot control involves the processes of learning and adaptation;
  • The field of computational architectures for autonomous robots encompasses a wide range of methodologies and frameworks that are specifically designed to facilitate the autonomous capabilities of robots;
  • Path optimization and multi-level path planning for the navigation algorithm;
  • The human–robot collaboration and physical interaction, surveillance, or exploration of unknown spaces with mobile agents.

Dr. Ionica Oncioiu
Dr. Lucian Ştefǎniţǎ Grigore
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

  • path planning
  • mobile robotics
  • autonomous mobile robots
  • multi-modal sensorial systems for robot navigation
  • robot motion models
  • localization and mapping
  • robots and control systems
  • IoT networks
  • intelligent transportation
  • sensor/data fusion
  • humanoid robots
  • network security

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Related Special Issue

Published Papers (4 papers)

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Research

31 pages, 38930 KiB  
Article
Path Planning for Mobile Robots Based on the Improved DAPF-QRRT* Strategy
by Wenhao Liu, Hongyuan Wu, Wentao Xiong, Xiaopeng Li, Bofan Cai, Shengdong Yu and Jinyu Ma
Electronics 2024, 13(21), 4233; https://doi.org/10.3390/electronics13214233 - 29 Oct 2024
Viewed by 777
Abstract
The rapidly exploring random tree star (RRT*) algorithm is widely used to solve path planning problems. However, the RRT* algorithm and its variants fall short of achieving a balanced consideration of path quality and safety. To address this issue, an improved discretized artificial [...] Read more.
The rapidly exploring random tree star (RRT*) algorithm is widely used to solve path planning problems. However, the RRT* algorithm and its variants fall short of achieving a balanced consideration of path quality and safety. To address this issue, an improved discretized artificial potential field-QRRT* (IDAPF-QRRT*) path planning strategy is introduced. Initially, the APF method is integrated into the Quick-RRT* (Q-RRT*) algorithm, utilizing the attraction of goal points and the repulsion of obstacles to optimize the tree expansion process, swiftly achieving superior initial solutions. Subsequently, a triangle inequality-based path reconnection mechanism is introduced to create and reconnect path points, optimize the path length, and accelerate the generation of sub-optimal paths. Finally, by refining the traditional APF method, a repulsive orthogonal vector field is obtained, achieving the orthogonalization between repulsive and attractive vector fields. This places key path points within the optimized vector field and adjusts their positions, thereby enhancing path safety. Compared to the Q-RRT* algorithm, the DPF-QRRT* algorithm achieves a 37.66% reduction in the time taken to achieve 1.05 times the optimal solution, and the IDAPF-QRRT* strategy nearly doubles generated path safety. Full article
(This article belongs to the Special Issue Path Planning for Mobile Robots, 2nd Edition)
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24 pages, 15090 KiB  
Article
Multi-Agent Collaborative Path Planning Algorithm with Multiple Meeting Points
by Jianlin Mao, Zhigang He, Dayan Li, Ruiqi Li, Shufan Zhang and Niya Wang
Electronics 2024, 13(16), 3347; https://doi.org/10.3390/electronics13163347 - 22 Aug 2024
Viewed by 917
Abstract
Traditional multi-agent path planning algorithms often lead to path overlap and excessive energy consumption when dealing with cooperative tasks due to the single-agent-single-task configuration. For this reason, the “many-to-one” cooperative planning method has been proposed, which, although improved, still faces challenges in the [...] Read more.
Traditional multi-agent path planning algorithms often lead to path overlap and excessive energy consumption when dealing with cooperative tasks due to the single-agent-single-task configuration. For this reason, the “many-to-one” cooperative planning method has been proposed, which, although improved, still faces challenges in the vast search space for meeting points and unreasonable task handover locations. This paper proposes the Cooperative Dynamic Priority Safe Interval Path Planning with a multi-meeting-point and single-meeting-point solving mode switching (Co-DPSIPPms) algorithm to achieve multi-agent path planning with task handovers at multiple or single meeting points. First, the initial priority is set based on the positional relationships among agents within the cooperative group, and the improved Fermat point method is used to locate multiple meeting points quickly. Second, considering that agents must pick up sub-tasks or conduct task handovers midway, a segmented path planning strategy is proposed to ensure that cooperative agents can efficiently and accurately complete task handovers. Finally, an automatic switching strategy between multi-meeting-point and single-meeting-point solving modes is designed to ensure the algorithm’s success rate. Tests show that Co-DPSIPPms outperforms existing algorithms in 1-to-1 and m-to-1 cooperative tasks, demonstrating its efficiency and practicality. Full article
(This article belongs to the Special Issue Path Planning for Mobile Robots, 2nd Edition)
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27 pages, 762 KiB  
Article
Path Planning Techniques for Real-Time Multi-Robot Systems: A Systematic Review
by Nour AbuJabal, Tamer Rabie, Mohammed Baziyad, Ibrahim Kamel and Khawla Almazrouei
Electronics 2024, 13(12), 2239; https://doi.org/10.3390/electronics13122239 - 7 Jun 2024
Cited by 1 | Viewed by 3274
Abstract
A vast amount of research has been conducted on path planning over recent decades, driven by the complexity of achieving optimal solutions. This paper reviews multi-robot path planning approaches and presents the path planning algorithms for various types of robots. Multi-robot path planning [...] Read more.
A vast amount of research has been conducted on path planning over recent decades, driven by the complexity of achieving optimal solutions. This paper reviews multi-robot path planning approaches and presents the path planning algorithms for various types of robots. Multi-robot path planning approaches have been classified as deterministic approaches, artificial intelligence (AI)-based approaches, and hybrid approaches. Bio-inspired techniques are the most employed approaches, and artificial intelligence approaches have gained more attention recently. However, multi-robot systems suffer from well-known problems such as the number of robots in the system, energy efficiency, fault tolerance and robustness, and dynamic targets. Deploying systems with multiple interacting robots offers numerous advantages. The aim of this review paper is to provide a comprehensive assessment and an insightful look into various path planning techniques developed in multi-robot systems, in addition to highlighting the basic problems involved in this field. This will allow the reader to discover the research gaps that must be solved for a better path planning experience for multi-robot systems. Full article
(This article belongs to the Special Issue Path Planning for Mobile Robots, 2nd Edition)
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23 pages, 4827 KiB  
Article
Motion Coordination of Multiple Autonomous Mobile Robots under Hard and Soft Constraints
by Spyridon Anogiatis, Panagiotis S. Trakas and Charalampos P. Bechlioulis
Electronics 2024, 13(11), 2128; https://doi.org/10.3390/electronics13112128 - 29 May 2024
Cited by 1 | Viewed by 963
Abstract
This paper presents a distributed approach to the motion control problem for a platoon of unicycle robots moving through an unknown environment filled with static obstacles under multiple hard and soft operational constraints. Each robot has an onboard camera to determine its relative [...] Read more.
This paper presents a distributed approach to the motion control problem for a platoon of unicycle robots moving through an unknown environment filled with static obstacles under multiple hard and soft operational constraints. Each robot has an onboard camera to determine its relative position in relation to its predecessor and proximity sensors to detect and avoid nearby obstascles. Moreover, no robot apart from the leader can independently localize itself within the given workspace. To overcome this limitation, we propose a novel distributed control protocol for each robot of the fleet, utilizing the Adaptive Performance Control (APC) methodology. By utilizing the APC approach to address input constraints via the on-line modification of the error specifications, we ensure that each follower effectively tracks its predecessor without encountering collisions with obstacles, while simultaneously maintaining visual contact with its preceding robot, thus ensuring the inter-robot visual connectivity. Finally, extensive simulation results are presented to demonstrate the effectiveness of the presented control system along with a real-time experiment conducted on an actual robotic system to validate the feasibility of the proposed approach in real-world scenarios. Full article
(This article belongs to the Special Issue Path Planning for Mobile Robots, 2nd Edition)
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