Optimal SUAS Path Planning in Three-Dimensional Constrained Environments

Michael D. Zollars, R. Cobb, David J. Grymin
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引用次数: 6

Abstract

Small Unmanned Aircraft Systems have grown in autonomy and capability and continue to complement Department of Defense mission objectives. Teaming unmanned aircraft with manned vehicles can expand mission profiles and reduce risk to human life. To fully leverage unmanned systems, vehicles must be efficient and autonomous in path planning development. The work herein explores direct orthogonal collocation optimal control techniques combined with fast geometric path planning algorithms to reduce computation time and increase solution accuracy for small unmanned aircraft systems path planning missions. Previous work in the two-dimensional plane demonstrated a methodology to provide optimal flight paths through defined simplex corridors and simplified the optimal control parameter bounds by formulating the problem in the barycentric coordinate system. These methodologies are extended in this paper for three-dimensional flight and are solved with two different formulations for flight in an urban environment. The first formulation solves the constrained optimal control problem using a single phase while modeling the building constraints with superquadric functions. The second formulation implements the simplex methodology, eliminating polygonal constraints from the search domain, and solving the optimal path in a multiple phase approach. Results illustrate the benefits gained in computation time and accuracy when implementing simplex methods into the optimal control design and provide a foundation for closing the gap to real-time, onboard operations for unmanned vehicle path planning.
三维约束环境下SUAS最优路径规划
小型无人机系统在自主性和能力方面不断增长,并继续补充国防部的任务目标。无人驾驶飞机与载人飞行器的组合可以扩大任务范围,减少对人类生命的威胁。为了充分利用无人驾驶系统,车辆必须在路径规划开发中高效和自主。研究了直接正交配置最优控制技术与快速几何路径规划算法相结合,以减少小型无人机系统路径规划任务的计算时间,提高求解精度。先前在二维平面上的工作展示了一种通过定义的单纯形走廊提供最优飞行路径的方法,并通过在质心坐标系中表述问题来简化最优控制参数边界。本文将这些方法扩展到三维飞行中,并用两种不同的公式求解城市环境中的飞行。第一个公式用超二次函数对建筑约束进行建模,用单相求解约束最优控制问题。第二种方法采用单纯形法,消除搜索域的多边形约束,采用多阶段方法求解最优路径。结果表明,在最优控制设计中实施单纯形方法在计算时间和精度方面所获得的好处,并为缩小无人驾驶车辆路径规划与实时车载操作的差距提供了基础。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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