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FusionPlanner: A multi-task motion planner for mining trucks via multi-sensor fusion

文献类型：期刊论文

作者Teng, Siyu7,8; Li, Luxi7,8; Li, Yuchen7,8; Hu, Xuemin6; Li, Lingxi4,5; Ai, Yunfeng3,5; Chen, Long1,2,5
刊名MECHANICAL SYSTEMS AND SIGNAL PROCESSING
出版日期2024-02-15
卷号208页码:18
ISSN号0888-3270
关键词Autonomous driving Motion planning Simulation Multi-task Multi-sensor
DOI10.1016/j.ymssp.2023.111051
通讯作者Ai, Yunfeng() ; Chen, Long(long.chen@ic.ac.cn)
英文摘要In recent years, significant achievements have been made in motion planning for intelligent vehicles. However, as a typical unstructured environment, open -pit mining attracts limited attention due to its complex operational conditions and adverse environmental factors. A comprehensive paradigm for unmanned transportation in open -pit mines is proposed in this research. Firstly, we propose a multi -task motion planning algorithm, called FusionPlanner, for autonomous mining trucks by the multi -sensor fusion method to adapt both lateral and longitudinal control tasks for unmanned transportation. Then, we develop a novel benchmark called MiningNav, which offers three validation approaches to evaluate the trustworthiness and robustness of well -trained algorithms in transportation roads of open -pit mines. Finally, we introduce the Parallel Mining Simulator (PMS), a new high-fidelity simulator specifically designed for open -pit mining scenarios. PMS enables the users to manage and control open -pit mine transportation from both the single -truck control and multi -truck scheduling perspectives. The performance of FusionPlanner is tested by MiningNav in PMS, and the empirical results demonstrate a significant reduction in the number of collisions and takeovers of our planner. We anticipate our unmanned transportation paradigm will bring mining trucks one step closer to trustworthiness and robustness in continuous round-the-clock unmanned transportation.
资助项目National Natural Science Foundation of China[62373356] ; National Natural Science Foundation of China[62273135] ; Natural Science Foundation of Hubei Province in China[2021CFB460]
WOS研究方向Engineering
语种英语
出版者ACADEMIC PRESS LTD- ELSEVIER SCIENCE LTD
WOS记录号WOS:001153220800001
资助机构National Natural Science Foundation of China ; Natural Science Foundation of Hubei Province in China
源URL[http://ir.ia.ac.cn/handle/173211/55521]  
专题多模态人工智能系统全国重点实验室
通讯作者Ai, Yunfeng; Chen, Long
作者单位1.Chinese Acad Sci, Inst Automat, State Key Lab Mulimodal Artificial Intelligence S, Beijing, Peoples R China
2.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing, Peoples R China
3.Univ Chinese Acad Sci, Sch Artificial Intelligence, Beijing, Peoples R China
4.IUPUI, Dept Elect & Comp Engn, Indianapolis, IN USA
5.Waytous Inc, Beijing, Peoples R China
6.Hubei Univ, Sch Artificial Intelligence, Wuhan, Peoples R China
7.BNU HKBU United Int Coll, Dept Comp Sci, Zhuhai, Peoples R China
8.Hong Kong Baptist Univ, Dept Comp Sci, Hong Kong, Peoples R China
推荐引用方式
GB/T 7714		 Teng, Siyu,Li, Luxi,Li, Yuchen,et al. FusionPlanner: A multi-task motion planner for mining trucks via multi-sensor fusion[J]. MECHANICAL SYSTEMS AND SIGNAL PROCESSING,2024,208:18.
APA Teng, Siyu.,Li, Luxi.,Li, Yuchen.,Hu, Xuemin.,Li, Lingxi.,...&Chen, Long.(2024).FusionPlanner: A multi-task motion planner for mining trucks via multi-sensor fusion.MECHANICAL SYSTEMS AND SIGNAL PROCESSING,208,18.
MLA Teng, Siyu,et al."FusionPlanner: A multi-task motion planner for mining trucks via multi-sensor fusion".MECHANICAL SYSTEMS AND SIGNAL PROCESSING 208(2024):18.

入库方式： OAI收割

来源：自动化研究所

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