arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2009.07404cs.ROcs.SYeess.SY

Cell A* for Navigation of Unmanned Aerial Vehicles in Partially-known Environments

Clemson University(克莱姆森大学)

Wenjian Hao, Rongyao Wang, Alexander Krolicki, Yiqiang Han

英文摘要:

Proper path planning is the first step of robust and efficient autonomous navigation for mobile robots. Meanwhile, it is still challenging for robots to work in a complex environment without complete prior information. This paper presents an extension to the A* search algorithm and its variants to make the path planning stable with less computational burden while handling long-distance tasks. The implemented algorithm is capable of online searching for a collision-free and smooth path when heading to the defined goal position. This paper deploys the algorithm on the autonomous drone platform and implements it on a remote control car for algorithm efficiency validation.

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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