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Artificial potential field guided jps algorithm for fast optimal path planning in cluttered environments

JOURNAL OF THE BRAZILIAN SOCIETY OF MECHANICAL SCIENCES AND ENGINEERING 2022年第12期44卷 1-14页

作者： Su, Qinghua Ma, Shaobo Wang, Liyong Song, Yue Wang, Haodong Li, Boxiong Yang, Ying Beijing Informat Sci & Technol Univ Key Lab Modern Measurement & Control Technol Minist Educ Beijing 100192 Peoples R China

This paper focuses on the path planning improvement for mobile robots in cluttered environments. Due to the uncertainty of searching direction in traditional path planning algorithms, each node often searches for its following path node in irrelevant directions, which increases the time cost and the number of invalid nodes. In this study, an artificial potential field guided jump point search algorithm is proposed to solve this low-efficiency problem. This method builds an APF and a direction map, which represent resultant force distribution and node directionality to the target node, respectively. Then, with consideration of APF influence and direction map guidance, an expansion direction priority for path planning is calculated, which guides and improves the search for subsequent jump points. To evaluate its performance and efficiency, the APF-jps algorithm is compared with the conventional jps, RRT, APF and 8-domains A* algorithms in simulation and mobile robot experiments. The experimental results indicate that the APF-jps algorithm not only plans the shortest available path with the least time cost, but also reaches the highest node utilization rate. Comparing with the conventional jps algorithm, which ranks second in overall performance, both the number of key nodes and the path planning time decrease by 45.0% and 53.8%, respectively, while the node utilization rate increases by 23.4%. Therefore, the APF-jps algorithm shows its advantages in path planning, mainly by reducing the system computational load, improving the real-time performance, and increasing the mobile robot endurance time.

关键词： Path planning jps algorithm APF algorithm Mobile robot

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Research on Path Planning Based on Improved jps algorithm 5

Research on Path Planning Based on Improved JPS Algorithm

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5th International Conference on Robotics, Intelligent Control and Artificial Intelligence, RICAI 2023

作者： Li, YiLin Li, Yi School of Computer Science Sichuan University Chengdu China

ISBN: (纸本)9798350357950

In order to address issues in the jps pathfinding algorithm such as the search for unnecessary jump points, frequent jump point selections, and the lack of environmental information regarding the target location, this paper proposes a selectively bidirectional jps pathfinding algorithm based on a conditionally depth-first search and a biased selection towards the target point. The bidirectional search strategy of this algorithm prioritizes unidirectional searches approaching the target point, conducting in-depth searches towards the target until a change in the direction towards the target point occurs. The results indicate that the improved jps algorithm, compared to the traditional jps algorithm and bidirectional jps algorithm, exhibits fewer selected jump points, shorter pathfinding times, and significantly enhances the efficiency of global path planning. © 2023 IEEE.

关键词： Bidirectional Search Depth-First Search jps algorithm Mobile Robot Path Planning

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Vision-based initial localization of AGV and path planning with PO-jps algorithm

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EGYPTIAN INFORMATICS JOURNAL 2024年 27卷

作者： Wang, Zheng Tu, Hangyao Chan, Sixian Huang, Chengkan Zhao, Yanwei Hangzhou City Univ Sch Comp & Comp Sci Hangzhou Peoples R China Zhejiang Univ Technol Sch Comp Sci & Technol Hangzhou Peoples R China Hangzhou City Univ Sch Engn Hangzhou 310015 Peoples R China

In recent years, robot path planning has gained high attention. The traditional adaptive Monte Carlo localization (AMCL) has such problems as limitations in global localization, and incomplete path and time-consuming problem in path planning due to too much calculation of meaningless nodes by the jump point search (jps) algorithm. In view of the above problems, this paper proposed a method for vision-based initial localization of automated guided vehicle (AGV) and path planning with (pruning optimization) PO-jps algorithm. The core contents include: vision-based AMCL localization module and improved jps algorithm based on pruning optimization. Firstly, Oriented FAST and Rotated BRIEF (ORB) features are extracted from the images collected by vision, and coordinates are localized with the features, coupled with the initial map by laser SLAM, to construct a bag-of-words (BoW) library of features. The key frame most similar to the current one is obtained by comparing the similarity between the current and historical frames in the BoW library. The Euler transformation between these two frames is calculated, to carry out pose estimation. This pose, as an initial value, is provided to the AMCL for particle iteration. Secondly, in the path planning stage, an improved jps algorithm based on pruning optimization is proposed, and a strategy that the repeated intermediate inflection points in the complemented path after pathfinding are deleted is designed. Therefore, while a complete path is obtained, the calculation workload and memory consumption for meaningless nodes during node extension are reduced successfully, and the efficiency of the pathfinding algorithm is raised. Finally, verification of the method proposed in this paper is completed through a large number of simulations and physical experiments, which saved 17.7% of the time compared to the original jps algorithm and 279.6% to the A* algorithm.

关键词： AMCL localization Visual feature jps algorithm Path planning Pruning optimization

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Improved jps algorithm Using New Jump Point for Path Planning of Mobile Robot 16

Improved JPS Algorithm Using New Jump Point for Path Plannin...

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16th IEEE International Conference on Mechatronics and Automation (IEEE ICMA)

作者： Zheng, Xue Tu, Xiaowei Yang, Qinghua Shanghai Univ Dept Mechatron Engn & Automat Shanghai Peoples R China

ISBN: (纸本)9781728116976

In view of the discussion of robot collision in complex environment due to control or positioning error and robot size, this paper presents a jump point search algorithm with safe distance(SD-jps) for path planning. Based on the fast jump point search method, a new definition of the jump point and a node domain matrix are proposed to improve the jps algorithm. The SD-jps algorithm can select the any size of the node domain matrix to obtain the safe distance between the robot and the obstacle, and improve the flexibility of the robot movement. In addition, the different effects of SD-jps and A* algorithm on the number of search nodes, planed routes and planning time are also studied. Simulation results show that the improved jps algorithm can obtain different safety distances and plan the optimal path with shorter time.

关键词： Path Planning jps algorithm Jump Point Node Domain Matrix

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Fusion of Improved jps and A* algorithms for Tactical Path Planning 6

Fusion of Improved JPS and A* Algorithms for Tactical Path P...

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6th International Conference on Natural Language Processing (ICNLP)

作者： Feng, Ningning Yang, Gang Meng, Weida Hou, Guodong Xian Univ Posts & Telecommun Sch Commun & Informat Engn Xian Peoples R China

ISBN: (纸本)9798350349122;9798350349115

Aiming at the problem that it is difficult to obtain the optimal safe path when the special operations team performs missions in unfamiliar indoor environments, a tactical path planning approach incorporating the improved jps algorithm and the A* algorithm is proposed. Firstly, the algorithm performance is improved by improving the screening rules of the jump points of the jps algorithm and deleting the redundant intermediate jump points;secondly, the special warfare threat model is introduced into the heuristic function to avoid the enemy threat in the process of tactical path planning;in addition, considering the characteristics of the influence of environmental complexity on the jps algorithm, the threshold function of the jump points is designed, and the A* algorithm and the improved jps algorithm are fused to solve the problem of reduced efficiency caused by searching for too many jump points in a dense environment of the jps algorithm in the obstacles. Finally, experimental results show that the proposed algorithm reduces the exposed path length by 69.95% in the hazardous area during path planning, while the path planning time is reduced by 8.44%.

关键词： path planning jps algorithm A* algorithm tactical threat model jump point threshold function

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Improved jps Path Optimization for Mobile Robots Based on Angle-Propagation Theta* algorithm

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algorithmS 2022年第6期15卷 198-198页

作者： Luo, Yuan Lu, Jiakai Qin, Qiong Liu, Yanyu Chongqing Univ Posts & Telecommun Key Lab Optoelect Informat Sensing & Technol Chongqing 400065 Peoples R China

The Jump Point Search (jps) algorithm ignores the possibility of any-angle walking, so the paths found by the jps algorithm under the discrete grid map still have a gap with the real paths. To address the above problems, this paper improves the path optimization strategy of the jps algorithm by combining the viewable angle of the Angle-Propagation Theta* (AP Theta*) algorithm, and it proposes the AP-jps algorithm based on an any-angle pathfinding strategy. First, based on the jps algorithm, this paper proposes a vision triangle judgment method to optimize the generated path by selecting the successor search point. Secondly, the idea of the node viewable angle in the AP Theta* algorithm is introduced to modify the line of sight (LOS) reachability detection between two nodes. Finally, the paths are optimized using a seventh-order polynomial based on minimum snap, so that the AP-jps algorithm generates paths that better match the actual robot motion. The feasibility and effectiveness of this method are proved by simulation experiments and comparison with other algorithms. The results show that the path planning algorithm in this paper obtains paths with good smoothness in environments with different obstacle densities and different map sizes. In the algorithm comparison experiments, it can be seen that the AP-jps algorithm reduces the path by 1.61-4.68% and the total turning angle of the path by 58.71-84.67% compared with the jps algorithm. The AP-jps algorithm reduces the computing time by 98.59-99.22% compared with the AP-Theta* algorithm.

关键词： path planning robot trajectory optimization jps algorithm Angle-Propagation Theta* algorithm grid map

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An Improved Hybrid A* algorithm of Path Planning for Hotel Service Robot

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INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2023年第10期14卷 868-874页

作者： Cao, Xiaobing Xu, Yicen Yao, Yonghong Zhi, Chenbo Wuxi Inst Technol Sch Control Technol Wuxi Jiangsu Peoples R China Wuxi Vocat Inst Commerce Sch Intelligent Equipment & Automot Engn Wuxi 214153 Jiangsu Peoples R China Huawei Technol Co LTD Xian Res Inst Xian 710075 Shaanxi Peoples R China

Due to the increasing demand for unmanned in the hotel industry in recent years, how to efficiently use hotel service robots to further improve the efficiency of the hotel industry has become a hot research issue. To solve the problems of lengthy path-finding time and poor route security in conventional service robots in complex environments, the current study provides an improved A* path-finding algorithm for application in the hotel environment. Firstly, the conventional A* algorithm is combined with bidirectional search and Jump Point Search (JSP) algorithm, which makes the search more effective. Secondly, the traditional A* algorithm is combined with the security weight square matrix to make the path trajectory safer. A cubic spline interpolation is chosen to smoothen the transitions at the corners planned by the improved A* algorithm. Simulation experiments were done on grid maps with 10*10, 20*20 and 50*50 sizes. Compared with the conventional A* algorithm, the search time were decreased by 67%, 77% and 95% respectively. The number of search nodes was decreased by 80%, 76% and 95%, respectively. Meanwhile the distance between the robot and the obstacles was increased. The results indicate that the improved A* algorithm suggested in the present research can ensure the path trajectory safer while keeping the path search efficiency higher.

关键词： Path planning bidirectional A* algorithm jps algorithm security weight square matrix cubic spline interpolation method

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Local Path Planning of Driverless Car Navigation Based on Jump Point Search Method Under Urban Environment

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FUTURE INTERNET 2017年第3期9卷 51-51页

作者： Zhou, Kaijun Yu, Lingli Long, Ziwei Mo, Siyao Hunan Univ Commerce Mobile E Business Collaborat Innovat Ctr Hunan Pro Changsha 410205 Hunan Peoples R China Hunan Univ Commerce Key Lab Hunan Prov Mobile Business Intelligence Changsha 410205 Hunan Peoples R China Cent S Univ Sch Informat Sci & Engn Changsha 410083 Hunan Peoples R China

The Jump Point Search (jps) algorithm is adopted for local path planning of the driverless car under urban environment, and it is a fast search method applied in path planning. Firstly, a vector Geographic Information System (GIS) map, including Global Positioning System (GPS) position, direction, and lane information, is built for global path planning. Secondly, the GIS map database is utilized in global path planning for the driverless car. Then, the jps algorithm is adopted to avoid the front obstacle, and to find an optimal local path for the driverless car in the urban environment. Finally, 125 different simulation experiments in the urban environment demonstrate that jps can search out the optimal and safety path successfully, and meanwhile, it has a lower time complexity compared with the Vector Field Histogram (VFH), the Rapidly Exploring Random Tree (RRT), A*, and the Probabilistic Roadmaps (PRM) algorithms. Furthermore, jps is validated usefully in the structured urban environment.

关键词： driverless car jps algorithm GIS map structured urban environment

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Pokročilé metody plánování cesty mobilního robotu

Pokročilé metody plánování cesty mobilního robotu

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作者： Maňáková, Lenka Brno University of Technology

Tato práce je zaměřená na pokročilé metody plánování cesty mobilního robotu. V teoretické části se zaměřuje na popis vybraných grafových metod, které o jso... 详细信息

Tato práce je zaměřená na pokročilé metody plánování cesty mobilního robotu. V teoretické části se zaměřuje na popis vybraných grafových metod, které o jsou specifické tím, že zefektivňují proces hledání nejkratší cesty a to například redukcí počtu prozkoumaných uzlů stavového prostoru. V rámci praktické části bylo vytvořeno simulační prostředí v jazyce Python a v tomto prostředí pak byly implementovány vybrané algoritmy.

关键词： Plánování cesty mobilní robot A* algoritmus jps algoritmus Subgoal algoritmus bounding box. Path planning mobile robot A* algorithm jps algorithm Subgoal algorithm bounding box. Text

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