Nowadays, unmanned aerial vehicles or UAVs are being used for a wide range of tasks, including infrastructure inspection, automated monitoring and coverage. This paper investigates the problem of 3D inspection planning with an autonomous UAV agent which is subject to dynamical and sensing constraints. We propose a receding horizon 3D inspection planning control approach for generating optimal trajectories which enable an autonomous UAV agent to inspect a finite number of feature-points scattered on the surface of a cuboid-like structure of interest. The inspection planning problem is formulated as a constrained open-loop optimal control problem and is solved using mixed integer programming (MIP) optimization. Quantitative and qualitative evaluation demonstrates the effectiveness of the proposed approach.
翻译:现今, 无人机正在被用于各种任务,包括基础设施检测,自动化监控和覆盖。本文研究了一个问题:一个自动无人机代理人如何面对动态和感官约束进行 3D 检测规划。我们提出了一种逆推式 3D 检测规划控制方法,用于生成最佳轨迹,使得一个自动无人机代理人能够检测有限数量的分布在类立方体状感兴趣结构表面上的特征点。检测规划问题被制定为约束开环最优控制问题,并通过混合整数规划(MIP)进行求解。定量和定性评估证明了所提出方法的有效性。