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Conference Papers Year : 2017

Quadrotor-UAV optimal coverage path planning in cluttered environment with a limited onboard energy

Abstract

In this paper, a quadrotor optimal coverage planning approach in damaged area is considered. The quadrotor is assumed to visit a set of reachable points following the shortest path while avoiding the no-fly zones. The problem is solved by using a two-scale proposed algorithm. In the first scale, an efficient tool for cluttered environments based on optimal Rapidly-exploring Random Trees (RRT) approach, called multi-RRT∗ Fixed Node (RRT∗FN), is developed to define the shortest paths from each point to their neighbors. Using the pair-wise costs between points provided by the first-scale algorithm, in the second scale, the overall shortest path is obtained by solving the Traveling Salesman Problem (TSP) using Genetic Algorithms (GA). Taking into consideration the limited onboard energy, a second alternative based on the well-known Vehicle Routing Problem (VRP) is used. This latter is solved using the savings heuristic approach. The effectiveness of this proposed two-scale algorithm is demonstrated through numerical simulations and promising results are obtained.

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Dates and versions

hal-01716915 , version 1 (29-03-2020)

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Yasser Bouzid, Yasmina Bestaoui, Houria Siguerdidjane. Quadrotor-UAV optimal coverage path planning in cluttered environment with a limited onboard energy. 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2017), Sep 2017, Vancouver, Canada. pp.979--984, ⟨10.1109/IROS.2017.8202264⟩. ⟨hal-01716915⟩
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