Autonomous Path Finding and Obstacle Avoidance Method for Unmanned Construction Machinery
The working environment of construction machinery is harsh, and some operations are highly repetitive. The realization of intelligent construction machinery helps to improve economic efficiency and promote industrial development. Construction machinery is different from ordinary passenger vehicles....
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| Format: | Article |
| Language: | English |
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MDPI AG
2023-04-01
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| Series: | Electronics |
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| Online Access: | https://www.mdpi.com/2079-9292/12/9/1998 |
| _version_ | 1797602802763038720 |
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| author | Jiangdong Wu Haoling Ren Tianliang Lin Yu Yao Zhen Fang Chang Liu |
| author_facet | Jiangdong Wu Haoling Ren Tianliang Lin Yu Yao Zhen Fang Chang Liu |
| author_sort | Jiangdong Wu |
| collection | DOAJ |
| description | The working environment of construction machinery is harsh, and some operations are highly repetitive. The realization of intelligent construction machinery helps to improve economic efficiency and promote industrial development. Construction machinery is different from ordinary passenger vehicles. Aiming at the fact that the existing environmental perception data set cannot be directly applied to construction machinery, this paper establishes the corresponding data set in combination with the specific working conditions of construction machinery and carries out training based on the PointPillars network to realize the environmental perception function applicable to the working conditions of construction machinery. Most construction machinery runs on unstructured roads, and the existing passenger vehicle path planning algorithm is not applicable to construction machinery. Based on this, this paper uses a hybrid A* algorithm to achieve path planning that meets the kinematics of construction machinery and realizes real-time obstacle detection and avoidance. At the same time, this paper combines environmental perception with a path planning algorithm to provide a method of autonomous path finding and obstacle avoidance for construction machinery. Based on the improved pure pursuit algorithm, the high-precision motion control and established trajectory tracking of construction machinery are realized, which lays a certain foundation for the follow-up research and development of related intelligent technologies of construction machinery. |
| first_indexed | 2024-03-11T04:21:39Z |
| format | Article |
| id | doaj.art-e807f474a7f14d3eb2bb7f21ab7ea44b |
| institution | Directory Open Access Journal |
| issn | 2079-9292 |
| language | English |
| last_indexed | 2024-03-11T04:21:39Z |
| publishDate | 2023-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Electronics |
| spelling | doaj.art-e807f474a7f14d3eb2bb7f21ab7ea44b2023-11-17T22:47:19ZengMDPI AGElectronics2079-92922023-04-01129199810.3390/electronics12091998Autonomous Path Finding and Obstacle Avoidance Method for Unmanned Construction MachineryJiangdong Wu0Haoling Ren1Tianliang Lin2Yu Yao3Zhen Fang4Chang Liu5College of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, ChinaCollege of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, ChinaCollege of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, ChinaSchool of Mechanical Engineering and Automation, Beihang University, Beijing 102206, ChinaCollege of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, ChinaCollege of Mechanical Engineering and Automation, Huaqiao University, Xiamen 361021, ChinaThe working environment of construction machinery is harsh, and some operations are highly repetitive. The realization of intelligent construction machinery helps to improve economic efficiency and promote industrial development. Construction machinery is different from ordinary passenger vehicles. Aiming at the fact that the existing environmental perception data set cannot be directly applied to construction machinery, this paper establishes the corresponding data set in combination with the specific working conditions of construction machinery and carries out training based on the PointPillars network to realize the environmental perception function applicable to the working conditions of construction machinery. Most construction machinery runs on unstructured roads, and the existing passenger vehicle path planning algorithm is not applicable to construction machinery. Based on this, this paper uses a hybrid A* algorithm to achieve path planning that meets the kinematics of construction machinery and realizes real-time obstacle detection and avoidance. At the same time, this paper combines environmental perception with a path planning algorithm to provide a method of autonomous path finding and obstacle avoidance for construction machinery. Based on the improved pure pursuit algorithm, the high-precision motion control and established trajectory tracking of construction machinery are realized, which lays a certain foundation for the follow-up research and development of related intelligent technologies of construction machinery.https://www.mdpi.com/2079-9292/12/9/1998unmanned drivingconstruction machineryPointPillarshybrid A*improve pure pursuitautonomous routing |
| spellingShingle | Jiangdong Wu Haoling Ren Tianliang Lin Yu Yao Zhen Fang Chang Liu Autonomous Path Finding and Obstacle Avoidance Method for Unmanned Construction Machinery Electronics unmanned driving construction machinery PointPillars hybrid A* improve pure pursuit autonomous routing |
| title | Autonomous Path Finding and Obstacle Avoidance Method for Unmanned Construction Machinery |
| title_full | Autonomous Path Finding and Obstacle Avoidance Method for Unmanned Construction Machinery |
| title_fullStr | Autonomous Path Finding and Obstacle Avoidance Method for Unmanned Construction Machinery |
| title_full_unstemmed | Autonomous Path Finding and Obstacle Avoidance Method for Unmanned Construction Machinery |
| title_short | Autonomous Path Finding and Obstacle Avoidance Method for Unmanned Construction Machinery |
| title_sort | autonomous path finding and obstacle avoidance method for unmanned construction machinery |
| topic | unmanned driving construction machinery PointPillars hybrid A* improve pure pursuit autonomous routing |
| url | https://www.mdpi.com/2079-9292/12/9/1998 |
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