无人机群自主规划节能路径，低电量自动返航保安全。
Energy Aware and Safe Path Planning for Unmanned Aircraft Systems
- 结合模型预测控制与整数规划，动态优化多机路径。
- 低电量时自动返回起点，避免电池损坏，提升安全性。
- 引入能耗感知模型，防止越障穿角或跳跃，提升可行性。
本文提出一种面向多智能体无人飞行系统（UAS）的路径规划算法，实现对搜索区域的自主覆盖，同时兼顾障碍物规避、无人机自身能力及能耗特性。路径规划以能量效率为目标，优先选择低能耗操作。当某架无人机电量不足时，可自主返回初始位置安全着陆，防止电池受损。为此，将能耗感知的多旋翼模型融入基于模型预测控制与混合整数线性规划的路径规划框架中。此外，通过动态定义各UAS的可行区域，进一步优化规划效果，避免越障穿角或越跳现象。
原文摘要 · Abstract (English)
This paper proposes a path planning algorithm for multi-agent unmanned aircraft systems (UASs) to autonomously cover a search area, while considering obstacle avoidance, as well as the capabilities and energy consumption of the employed unmanned aerial vehicles. The path planning is optimized in terms of energy efficiency to prefer low energy-consuming maneuvers. In scenarios where a UAS is low on energy, it autonomously returns to its initial position for a safe landing, thus preventing potential battery damage. To accomplish this, an energy-aware multicopter model is integrated into a path planning algorithm based on model predictive control and mixed integer linear programming. Besides factoring in energy consumption, the planning is improved by dynamically defining feasible regions for each UAS to prevent obstacle corner-cutting or over-jumping.
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