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

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arxiv 2009.07404 v1 pith:4JMLE5P6 submitted 2020-09-16 cs.RO cs.SYeess.SY

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

classification cs.RO cs.SYeess.SY
keywords algorithmpathautonomousnavigationplanningrobotsaerialburden
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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