Path Planning Fusion Algorithm for Indoor Robot Based on Feature Map
In order to utilize the advantage of the feature map in calculating efficiency and solve the problem that the traditional dynamic window approach is sensitive to global parameters, a path planning fusion algorithm based on feature map is proposed. A feature map expression applicable to path planning...
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| Format: | Article |
| Language: | zho |
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Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press
2023-11-01
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| Series: | Jisuanji kexue yu tansuo |
| Subjects: | |
| Online Access: | http://fcst.ceaj.org/fileup/1673-9418/PDF/2207001.pdf |
| _version_ | 1797633133742391296 |
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| author | LIU Peng, REN Gongchang |
| author_facet | LIU Peng, REN Gongchang |
| author_sort | LIU Peng, REN Gongchang |
| collection | DOAJ |
| description | In order to utilize the advantage of the feature map in calculating efficiency and solve the problem that the traditional dynamic window approach is sensitive to global parameters, a path planning fusion algorithm based on feature map is proposed. A feature map expression applicable to path planning is given, and the detection of obstacles in the feature map is achieved by improving the calculation method of the distance between the robot and the obstacles. Combined with the basic principle of the Bug algorithm and the properties of line segment features, the searching and optimization algorithm is used to search the global feasible path first, and then the key nodes of the global optimal path are obtained by node optimization, and solutions are proposed for the problems of search direction selection at internal and external corner points and obstacle endpoint bypassing. To address the problem of high sensitivity of the traditional dynamic window approach to global parameters, the degree of influence of the parameters in the objective function on the planned path when the robot is at different positions is analyzed, and the original objective function is improved using the dynamic parameter approach. When the algorithms are fused, the calculation method of direction function in the objective function is improved in order to solve the problem that the robot may slow down in the intermediate nodes of the path. The simulation experiment verifies that the searching optimization algorithm is effective, the improved dynamic window approach reduces the sensitivity of parameters, and the fusion algorithm has a greater advantage in computational efficiency, with a maximum reduction of 79.27% and a minimum reduction of 43.16% in computational time consumption, and the robot moves more smoothly. |
| first_indexed | 2024-03-11T11:49:44Z |
| format | Article |
| id | doaj.art-553c223227a743e483f41ccf550f3887 |
| institution | Directory Open Access Journal |
| issn | 1673-9418 |
| language | zho |
| last_indexed | 2024-03-11T11:49:44Z |
| publishDate | 2023-11-01 |
| publisher | Journal of Computer Engineering and Applications Beijing Co., Ltd., Science Press |
| record_format | Article |
| series | Jisuanji kexue yu tansuo |
| spelling | doaj.art-553c223227a743e483f41ccf550f38872023-11-09T08:18:08ZzhoJournal of Computer Engineering and Applications Beijing Co., Ltd., Science PressJisuanji kexue yu tansuo1673-94182023-11-0117112755276610.3778/j.issn.1673-9418.2207001Path Planning Fusion Algorithm for Indoor Robot Based on Feature MapLIU Peng, REN Gongchang0College of Mechanical and Electrical Engineering, Shaanxi University of Science and Technology, Xi’an 710021, ChinaIn order to utilize the advantage of the feature map in calculating efficiency and solve the problem that the traditional dynamic window approach is sensitive to global parameters, a path planning fusion algorithm based on feature map is proposed. A feature map expression applicable to path planning is given, and the detection of obstacles in the feature map is achieved by improving the calculation method of the distance between the robot and the obstacles. Combined with the basic principle of the Bug algorithm and the properties of line segment features, the searching and optimization algorithm is used to search the global feasible path first, and then the key nodes of the global optimal path are obtained by node optimization, and solutions are proposed for the problems of search direction selection at internal and external corner points and obstacle endpoint bypassing. To address the problem of high sensitivity of the traditional dynamic window approach to global parameters, the degree of influence of the parameters in the objective function on the planned path when the robot is at different positions is analyzed, and the original objective function is improved using the dynamic parameter approach. When the algorithms are fused, the calculation method of direction function in the objective function is improved in order to solve the problem that the robot may slow down in the intermediate nodes of the path. The simulation experiment verifies that the searching optimization algorithm is effective, the improved dynamic window approach reduces the sensitivity of parameters, and the fusion algorithm has a greater advantage in computational efficiency, with a maximum reduction of 79.27% and a minimum reduction of 43.16% in computational time consumption, and the robot moves more smoothly.http://fcst.ceaj.org/fileup/1673-9418/PDF/2207001.pdfpath planning; feature map; bug algorithm; dynamic window approach; fusion algorithm |
| spellingShingle | LIU Peng, REN Gongchang Path Planning Fusion Algorithm for Indoor Robot Based on Feature Map Jisuanji kexue yu tansuo path planning; feature map; bug algorithm; dynamic window approach; fusion algorithm |
| title | Path Planning Fusion Algorithm for Indoor Robot Based on Feature Map |
| title_full | Path Planning Fusion Algorithm for Indoor Robot Based on Feature Map |
| title_fullStr | Path Planning Fusion Algorithm for Indoor Robot Based on Feature Map |
| title_full_unstemmed | Path Planning Fusion Algorithm for Indoor Robot Based on Feature Map |
| title_short | Path Planning Fusion Algorithm for Indoor Robot Based on Feature Map |
| title_sort | path planning fusion algorithm for indoor robot based on feature map |
| topic | path planning; feature map; bug algorithm; dynamic window approach; fusion algorithm |
| url | http://fcst.ceaj.org/fileup/1673-9418/PDF/2207001.pdf |
| work_keys_str_mv | AT liupengrengongchang pathplanningfusionalgorithmforindoorrobotbasedonfeaturemap |