Coverage of an inaccessible or difficult terrain with potential health and safety hazards, such as in a volcanic region, is difficult yet crucial from scientific and meteorological perspectives. Areas contained within this region can provide us with different types of 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,无法进入的或困难的地形,如火山地区,具有潜在的健康和安全危险,很难覆盖,但从科学和气象的角度来看,最优化问题十分关键,因为从科学和气象的角度来看,该区域内的地区可以提供不同种类的重要宝贵信息;我们提出了一个算法,以无人驾驶飞行器(无人驾驶飞行器)最佳覆盖哈瓦伊伊岛的火山地区;指定目标地区为非统一覆盖重要分数分布区;对于无人驾驶飞行器的特定电池能力,优化问题寻求一条途径,最大限度地扩大总覆盖面积和累计重要性分数,同时对同一地区的重新考察进行处罚;根据现有功率和覆盖范围信息图,为无人驾驶飞行器制作轨迹;最佳轨迹将未使用的电池功率降至最低,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重力编程解决;竞争优化问题的细节与分析和模拟结果一起讨论,以证明拟议的算法是否适用。