Multi-robot path planning for smart access of distributed charging points in map

Ravankar, Abhijeet; Ravankar, Ankit A.; Watanabe, Michiko; Hoshino, Yohei; Rawankar, Arpit

doi:10.1007/s10015-020-00612-8

Cited by 14 publications

(8 citation statements)

References 20 publications

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“…However, classical path planning approaches continue to be relevant and serve as a valuable foundation for modern path planning techniques. A variety of deterministic path planning techniques have been applied, including cell decomposition techniques [35][36][37][38][39][40][41], artificial potential field techniques [46][47][48], and sampling-based techniques [44,45]. The subsequent sections will explore the three subdivisions of traditional methods.…”

Section: Deterministic Approachesmentioning

confidence: 99%

Path Planning Techniques for Real-Time Multi-Robot Systems: A Systematic Review

AbuJabal,

Rabie,

Baziyad

et al. 2024

Electronics

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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.

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Section: Deterministic Approachesmentioning

confidence: 99%

Path Planning Techniques for Real-Time Multi-Robot Systems: A Systematic Review

AbuJabal,

Rabie,

Baziyad

et al. 2024

Electronics

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“…Both R and T are defined as 3 × 4 matrices, which contain translation and rotation information, respectively, as shown in (14). (14) Eliminate s with the last line to get two constraints, shown in (15) as follows: (15) To simplify the representation, the row vector T is defined as (16) Therefore, the two constraints can be rewritten as follows: (17) The characteristic points of each charging port can be given by the two constraint equations in (17). We can obtain the following system of equations when the number of characteristic points of charging port is equal to N: (18) It can be noted from (18) that with this method, at least six characteristic points of the charging port are needed to complete the pose calculation of the charging port.…”

Section: ) Solving the Pose Of The Charging Portmentioning

confidence: 99%

Research on Fast Identification and Location of Contour Features of Electric Vehicle Charging Port in Complex Scenes

et al. 2022

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The maturity of automatic driving and parking technologies is gradually driving electric vehicle charging toward automation. The primary condition of automatic charging that has a high significance is the identification of electric vehicle charging ports. This research proposes an automatic system for the identification and positioning of charging ports of electric vehicles. The system is mainly divided into rough and precise positioning. The former is based on the Hough circle and the Hough line, and locates the position information of the charging port. The latter uses the Canny operator to obtain the contour information of the original and gradient images respectively. All the contours of the two images are fitted into ellipses by the quadratic curve standardization (QCS) method, and irrelevant ellipses are screened out. Finally, the perspective-n-point (PNP) algorithm is used to locate the pose information of the charging port. The aubo-i10 6-DOF articulated robot is used to test the recognition and insertion accuracies in different environments. The results show that the average recognition rate of rough positioning is 97.9%, the average displacement error of precise positioning in X, Y and Z directions are 0.60, 0.83 and 1.23mm, respectively, and the average angle errors in RX, RY and RZ directions are 1.19, 0.97 and 0.50 degrees, respectively. The average success rate is 94.8%. These results demonstrate that the proposed system meets the basic plug-in requirements of electric vehicle charging ports. INDEX TERMSAutomatic charging, electric vehicle charging port, pose estimation, monocular vision, non-cooperative characteristics P. Quan et al.: Research on Fast Identification and Location of Contour Features of Electric Vehicle Charging Port in Complex Scenes PENGKUN QUAN received the B.S. degree in mechanical engineering from the Tianjin Agricultural University, Tianjin, China, in 2017, and the M.D. degree in Agricultural Engineering from the Northwest A&F University, Xianyang, China, in 2019. He is currently pursuing the Ph.D. degree in mechanical engineering with the Harbin Institute of Technology, Harbin, China.He has published over 4 articles and won the first prize of China graduate electronic design competition in 2018. His current research interests include computer vision and cable-driven auto-charging robot for electric vehicles.

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“…VFH and APF will perform efficiently with dynamic and static obstacles in constrained settings. Numerous path planning methods that consider obstacles in unpredictable settings have been discussed in [ 22 , 30 , 31 ]. Ayawli et al [ 32 ] provided a path-planning method in an uncertain environment based on the Voronoi diagram and computation geometry technique (VD-CGT), employing VD and mathematical modeling, with a narrow rectangular area around the robot used to assess collisions.…”

Section: Background and Related Workmentioning

confidence: 99%

A Generalized Laser Simulator Algorithm for Mobile Robot Path Planning with Obstacle Avoidance

Muhammad

Ali

Turaev

et al. 2022

Sensors

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This paper aims to develop a new mobile robot path planning algorithm, called generalized laser simulator (GLS), for navigating autonomously mobile robots in the presence of static and dynamic obstacles. This algorithm enables a mobile robot to identify a feasible path while finding the target and avoiding obstacles while moving in complex regions. An optimal path between the start and target point is found by forming a wave of points in all directions towards the target position considering target minimum and border maximum distance principles. The algorithm will select the minimum path from the candidate points to target while avoiding obstacles. The obstacle borders are regarded as the environment’s borders for static obstacle avoidance. However, once dynamic obstacles appear in front of the GLS waves, the system detects them as new dynamic obstacle borders. Several experiments were carried out to validate the effectiveness and practicality of the GLS algorithm, including path-planning experiments in the presence of obstacles in a complex dynamic environment. The findings indicate that the robot could successfully find the correct path while avoiding obstacles. The proposed method is compared to other popular methods in terms of speed and path length in both real and simulated environments. According to the results, the GLS algorithm outperformed the original laser simulator (LS) method in path and success rate. With application of the all-direction border scan, it outperforms the A-star (A*) and PRM algorithms and provides safer and shorter paths. Furthermore, the path planning approach was validated for local planning in simulation and real-world tests, in which the proposed method produced the best path compared to the original LS algorithm.

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Multi-robot path planning for smart access of distributed charging points in map

Cited by 14 publications

References 20 publications

Path Planning Techniques for Real-Time Multi-Robot Systems: A Systematic Review

Path Planning Techniques for Real-Time Multi-Robot Systems: A Systematic Review

Research on Fast Identification and Location of Contour Features of Electric Vehicle Charging Port in Complex Scenes

A Generalized Laser Simulator Algorithm for Mobile Robot Path Planning with Obstacle Avoidance

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