Dynamic Path Planning of AGV Based on Kinematical Constraint A Algorithm and Following DWA Fusion Algorithms
In the field of AGV, a path planning algorithm is always a heated area. However, traditional path planning algorithms have many disadvantages. To solve these problems, this paper proposes a fusion algorithm that combines the kinematical constraint A* algorithm and the following dynamic window approa...
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| Published in | Sensors (Basel, Switzerland) Vol. 23; no. 8; p. 4102 |
|---|---|
| Main Authors | , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
Switzerland
MDPI AG
19.04.2023
MDPI |
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| Online Access | Get full text |
| ISSN | 1424-8220 1424-8220 |
| DOI | 10.3390/s23084102 |
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| Abstract | In the field of AGV, a path planning algorithm is always a heated area. However, traditional path planning algorithms have many disadvantages. To solve these problems, this paper proposes a fusion algorithm that combines the kinematical constraint A* algorithm and the following dynamic window approach algorithm. The kinematical constraint A* algorithm can plan the global path. Firstly, the node optimization can reduce the number of child nodes. Secondly, improving the heuristic function can increase efficiency of path planning. Thirdly, the secondary redundancy can reduce the number of redundant nodes. Finally, the B spline curve can make the global path conform to the dynamic characteristics of AGV. The following DWA algorithm can be dynamic path planning and allow the AGV to avoidance moving obstacle. The optimization heuristic function of the local path is closer to the global optimal path. The simulation results show that, compared with the fusion algorithm of traditional A* algorithm and traditional DWA algorithm, the fusion algorithm reduces the length of path by 3.6%, time of path by 6.7% and the number of turns of final path by 25%. |
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| AbstractList | In the field of AGV, a path planning algorithm is always a heated area. However, traditional path planning algorithms have many disadvantages. To solve these problems, this paper proposes a fusion algorithm that combines the kinematical constraint A* algorithm and the following dynamic window approach algorithm. The kinematical constraint A* algorithm can plan the global path. Firstly, the node optimization can reduce the number of child nodes. Secondly, improving the heuristic function can increase efficiency of path planning. Thirdly, the secondary redundancy can reduce the number of redundant nodes. Finally, the B spline curve can make the global path conform to the dynamic characteristics of AGV. The following DWA algorithm can be dynamic path planning and allow the AGV to avoidance moving obstacle. The optimization heuristic function of the local path is closer to the global optimal path. The simulation results show that, compared with the fusion algorithm of traditional A* algorithm and traditional DWA algorithm, the fusion algorithm reduces the length of path by 3.6%, time of path by 6.7% and the number of turns of final path by 25%. In the field of AGV, a path planning algorithm is always a heated area. However, traditional path planning algorithms have many disadvantages. To solve these problems, this paper proposes a fusion algorithm that combines the kinematical constraint A* algorithm and the following dynamic window approach algorithm. The kinematical constraint A* algorithm can plan the global path. Firstly, the node optimization can reduce the number of child nodes. Secondly, improving the heuristic function can increase efficiency of path planning. Thirdly, the secondary redundancy can reduce the number of redundant nodes. Finally, the B spline curve can make the global path conform to the dynamic characteristics of AGV. The following DWA algorithm can be dynamic path planning and allow the AGV to avoidance moving obstacle. The optimization heuristic function of the local path is closer to the global optimal path. The simulation results show that, compared with the fusion algorithm of traditional A* algorithm and traditional DWA algorithm, the fusion algorithm reduces the length of path by 3.6%, time of path by 6.7% and the number of turns of final path by 25%.In the field of AGV, a path planning algorithm is always a heated area. However, traditional path planning algorithms have many disadvantages. To solve these problems, this paper proposes a fusion algorithm that combines the kinematical constraint A* algorithm and the following dynamic window approach algorithm. The kinematical constraint A* algorithm can plan the global path. Firstly, the node optimization can reduce the number of child nodes. Secondly, improving the heuristic function can increase efficiency of path planning. Thirdly, the secondary redundancy can reduce the number of redundant nodes. Finally, the B spline curve can make the global path conform to the dynamic characteristics of AGV. The following DWA algorithm can be dynamic path planning and allow the AGV to avoidance moving obstacle. The optimization heuristic function of the local path is closer to the global optimal path. The simulation results show that, compared with the fusion algorithm of traditional A* algorithm and traditional DWA algorithm, the fusion algorithm reduces the length of path by 3.6%, time of path by 6.7% and the number of turns of final path by 25%. |
| Audience | Academic |
| Author | Yao, Daojin Yin, Xiong Zhou, Qian Zhao, Kangwen Cai, Ping Zhang, Yu |
| AuthorAffiliation | School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330000, China |
| AuthorAffiliation_xml | – name: School of Electrical and Automation Engineering, East China Jiaotong University, Nanchang 330000, China |
| Author_xml | – sequence: 1 givenname: Xiong orcidid: 0009-0008-0907-8118 surname: Yin fullname: Yin, Xiong – sequence: 2 givenname: Ping surname: Cai fullname: Cai, Ping – sequence: 3 givenname: Kangwen surname: Zhao fullname: Zhao, Kangwen – sequence: 4 givenname: Yu surname: Zhang fullname: Zhang, Yu – sequence: 5 givenname: Qian surname: Zhou fullname: Zhou, Qian – sequence: 6 givenname: Daojin surname: Yao fullname: Yao, Daojin |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37112443$$D View this record in MEDLINE/PubMed |
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| Snippet | In the field of AGV, a path planning algorithm is always a heated area. However, traditional path planning algorithms have many disadvantages. To solve these... |
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| SubjectTerms | A algorithm Agricultural production Algorithms DWA algorithm dynamic obstacle avoidance Efficiency Farm machinery global path planning Heuristic Kinematics Robots Vehicles |
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| Title | Dynamic Path Planning of AGV Based on Kinematical Constraint A Algorithm and Following DWA Fusion Algorithms |
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