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Time-Optimal Path Planning With Power Schedules for a Solar-Powered Ground Robot

机译:带有时间安排的太阳能地面机器人的时间最优路径规划

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This paper examines an integrated path planning and power management problem for a solar-powered unmanned ground vehicle (UGV). The proposed method seeks to minimize the travel time of the UGV through an area of known energy density by designing a smooth, heuristically optimized path and allocating the vehicle’s power among its electrical components, while the UGV harvests ambient energy along the designed path to satisfy with the mission’s strict energy constraints. A scalar field is first established to evaluate the solar radiation density at discrete locations. A modified particle swarm optimization method is applied to search for a minimal time path wherein the energy gathered is equal to or greater than the energy expended. The proposed modeling and optimization strategy is verified through computer simulation and experimental demonstration.
机译:本文研究了太阳能无人地面车辆(UGV)的综合路径规划和电源管理问题。所提出的方法旨在通过设计一条平滑的,启发式优化的路径并在其电气部件之间分配车辆的功率,来使UGV在已知能量密度区域内的行驶时间最小化,同时UGV沿着设计的路径收集环境能量以满足特派团严格的能源限制。首先建立标量场以评估离散位置的太阳辐射密度。将改进的粒子群优化方法应用于搜索最小时间路径,在该最小时间路径中,所收集的能量等于或大于所消耗的能量。通过计算机仿真和实验验证,验证了所提出的建模和优化策略。

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