arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2007.09633cs.RO
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Motion Planning for Heterogeneous Unmanned Systems under Partial Observation from UAV

College of Biosystems Engineering and Food Science, Zhejiang University(浙江大学生物系统工程与食品科学学院);Department of Ocean Science and Engineering, Southern University of Science and Technology(南方科技大学海洋科学与工程系);The State Key Laboratory of Turbulence and Complex Systems, Intelligent Biomimetic Design Lab, College of Engineering, Peking University(北京大学工学院湍流与复杂系统国家重点实验室智能仿生设计实验室);National Engineering Research Center for Software Engineering, Peking University(北京大学软件工程国家工程研究中心);Peng Cheng Laboratory(鹏城实验室)

Ci Chen, Yuanfang Wan, Baowei Li, Chen Wang, Guangming Xie, Huanyu Jiang

英文摘要:

For heterogeneous unmanned systems composed of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs), using UAVs serve as eyes to assist UGVs in motion planning is a promising research direction due to the UAVs' vast view scope. However, due to UAVs flight altitude limitations, it may be impossible to observe the global map, and motion planning in the local map is a POMDP (Partially Observable Markov Decision Process) problem. This paper proposes a motion planning algorithm for heterogeneous unmanned system under partial observation from UAV without reconstruction of global maps, which consists of two parts designed for perception and decision-making, respectively. For the perception part, we propose the Grid Map Generation Network (GMGN), which is used to perceive scenes from UAV's perspective and classify the pathways and obstacles. For the decision-making part, we propose the Motion Command Generation Network (MCGN). Due to the addition of memory mechanism, MCGN has planning and reasoning abilities under partial observation from UAVs. We evaluate our proposed algorithm by comparing with baseline algorithms. The results show that our method effectively plans the motion of heterogeneous unmanned systems and achieves a relatively high success rate.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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