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.
翻译:从科学和气象的角度来看,难以覆盖可能存在健康和安全危害的无法进入或具有挑战性的区域,如火山地区,很难覆盖,但从科学和气象的角度来看,这一问题至关重要。区域内的一些地区往往提供不同重要性的宝贵信息。我们用无人驾驶飞行器(UAV)提出一种算法,优化覆盖Hawai`i火山地区;指定目标地区为非统一覆盖区,分配重要分数。对于无人驾驶飞行器指定的电池容量,优化问题寻求一条途径,以最大限度地扩大总覆盖面积和累计重要分数,同时惩罚同一地区的重新审视。轨迹是根据现有功率和覆盖范围信息地图为无人驾驶飞行器而离线生成的轨迹。最佳轨迹将未使用的电池功率降至最小,同时强制将无人驾驶飞行器返回其起始位置。这一多目标优化问题通过连续的四极编程解决。竞争优化问题的细节与分析和模拟结果一起讨论,以证明拟议算法的适用性。