Online Path Planning For Autonomous Underwater Vehicles In Unknown Environments
2015 IEEE International Conference on Robotics and Automation (ICRA)(2015)
摘要
We present a framework for planning collision-free paths online for autonomous underwater vehicles (AUVs) in unknown environments. It is composed of three main modules (mapping, planning and mission handler) that incrementally explore the environment while solving start-to-goal queries. We use an octree-based representation of the environment and we extend the optimal rapidly-exploring random tree (RRT*) using concepts of anytime algorithms and lazy collision evaluation, thus including the capability to replan paths according to nearby obstacles perceived during the execution of the mission. To validate our approach, we plan paths for the SPARUS-II AUV, a torpedo-shaped vehicle performing autonomous missions in a 2-dimensional workspace. We demonstrate its feasibility with the SPARUS-II AUV in both simulation and real-world in-water trials.
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关键词
autonomous underwater vehicles,collision-free online path planning,mission handler,octree-based representation,start-to-goal queries,optimal rapidly-exploring random tree,RRT,mapping,anytime algorithms,lazy collision evaluation,SPARUS-II AUV,torpedo-shaped vehicle,autonomous missions,2-dimensional workspace,real-world in-water trials
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