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$ε^*$+ An Online Coverage Path Planning Algorithm for Energy-constrained Autonomous Vehicles

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Document pages: 6 pages

Abstract: This paper presents a novel algorithm, called $ epsilon^*$+, for onlinecoverage path planning of unknown environments using energy-constrainedautonomous vehicles. Due to limited battery size, the energy-constrainedvehicles have limited duration of operation time. Therefore, while executing acoverage trajectory, the vehicle has to return to the charging station for arecharge before the battery runs out. In this regard, the $ epsilon^*$+algorithm enables the vehicle to retreat back to the charging station based onthe remaining energy which is monitored throughout the coverage process. Thisis followed by an advance trajectory that takes the vehicle to a near byunexplored waypoint to restart the coverage process, instead of taking it backto the previous left over point of the retreat trajectory; thus reducing theoverall coverage time. The proposed $ epsilon^*$+ algorithm is an extension ofthe $ epsilon^*$ algorithm, which utilizes an Exploratory Turing Machine (ETM)as a supervisor to navigate the vehicle with back and forth trajectory forcomplete coverage. The performance of the $ epsilon^*$+ algorithm is validatedon complex scenarios using Player Stage which is a high-fidelity roboticsimulator.

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