An Online Coverage Path Planning Method for Sweeper Trucks in Dynamic Environments
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- 形態
- 価格
- 一般価格(税込):¥6,600 会員価格(税込):¥5,280
- 文献・情報種別
- SAE Paper
No.2021-01-0095
- 掲載ページ
- 1-8(Total 8 p)
- 発行年月
- 2021年 4月
- 出版社
- SAE International
- 言語
- 英語
- イベント
- SAE WCX Digital Summit 2021
書誌事項
著者(英) | 1) Weiyang Zhang, 2) Yong Sun, 3) Wenbo Yu, 4) MENG XU |
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勤務先(英) | 1) Isuzu Technical Center of America Inc., 2) Isuzu Technical Center of America Inc., 3) Isuzu Technical Center of America Inc., 4) Isuzu Technical Center of America Inc. |
抄録(英) | In this paper, a novel online coverage path planning (CPP) method for autonomous sweeper trucks in closed areas is proposed. This method can efficiently generate executable paths for sweeper trucks that cover all feasible uncleaned areas without getting tracked in dead-end, i.e., no backward behaviors required and avoid dynamic obstacles. To reach that end, a modified biological inspired neuron network method considering vehicle constrains is developed, where the dynamic of each neuron is determined by the shunting function. The path will be iteratively generated based on local neuron dynamics. In order to avoid dead-end, a detour algorithm combing with back iteration is introduced to search the nearest uncleaned area that can be reached within vehicle constrains. The proposed method is empirically approved to be computationally efficient and adaptive to maps with arbitrary shapes. The feasibility of generated paths is validated in simulations, where the pure pursuit method is applied to achieve path following. The truck model in the simulation achieves 100% coverage with reasonable cross-track errors. 翻訳 |