Path Planning for Optimal Coverage of Areas with Nonuniform Importance
Path Planning for Optimal Coverage of Areas with Nonuniform Importance
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DOI：
10.2514/6.2022-2546
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发表时间：
2021-10
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影响因子：
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通讯作者：
Gregory F. Snyder;Sachin Shriwastav;Dylan Morrison-Fogel;Zhuoyuan Song
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作者：
Gregory F. Snyder;Sachin Shriwastav;Dylan Morrison-Fogel;Zhuoyuan Song
从科学和气象的角度来看，覆盖一个难以进入或具有挑战性的地区，如火山地区，具有潜在的健康和安全危险，是困难的，但至关重要。该区域内的地区往往提供重要性不一的宝贵信息。我们提出了一种算法，以最佳覆盖夏威夷的火山地区与无人驾驶飞行器（UAV）。目标区域被分配有非均匀的覆盖重要性分数分布。对于指定的电池容量的无人机，优化问题寻求的路径，最大化的总覆盖区域和累积的重要性得分，同时惩罚重访相同的区域。基于可用功率和覆盖信息地图为UAV离线生成轨迹。最佳轨迹使未消耗的电池电量最小化，同时强制UAV返回其起始位置。这个多目标优化问题的解决，使用序列二次规划。竞争优化问题的细节进行了讨论沿着的分析和仿真结果证明所提出的算法的适用性。
Coverage of an inaccessible or challenging region with potential health and safety hazards, such as in a volcanic region, is difficult yet crucial from scientific and meteorological perspectives. Areas contained within the region often provide valuable information of varying importance. We present an algorithm to optimally cover a volcanic region in Hawai`i with an unmanned aerial vehicle (UAV). The target region is assigned with a nonuniform coverage importance score distribution. For a specified battery capacity of the UAV, the optimization problem seeks the path that maximizes the total coverage area and the accumulated importance score while penalizing the revisiting of the same area. Trajectories are generated offline for the UAV based on the available power and coverage information map. The optimal trajectory minimizes the unspent battery power while enforcing that the UAV returns to its starting location. This multi-objective optimization problem is solved by using sequential quadratic programming. The details of the competitive optimization problem are discussed along with the analysis and simulation results to demonstrate the applicability of the proposed algorithm.