Obstacle avoidance path planning for uncrewed aerial vehicles (UAVs), or drones, is rarely addressed in most flight path planning schemes, despite obstacles being a realistic condition. Obstacle avoidance can also be energy-intensive, making it a critical factor in efficient point-to-point drone flights. To address these gaps, we propose EcoFlight, an energy-efficient pathfinding algorithm that determines the lowest-energy route in 3D space with obstacles. The algorithm models energy consumption based on the drone propulsion system and flight dynamics. We conduct extensive evaluations, comparing EcoFlight with direct-flight and shortest-distance schemes. The simulation results across various obstacle densities show that EcoFlight consistently finds paths with lower energy consumption than comparable algorithms, particularly in high-density environments. We also demonstrate that a suitable flying speed can further enhance energy savings.

翻译：在大多数飞行路径规划方案中，无人飞行器（UAV，即无人机）的避障路径规划很少被涉及，尽管障碍物是现实存在的条件。避障也可能消耗大量能量，这使其成为高效点对点无人机飞行的关键因素。为弥补这些不足，我们提出了EcoFlight，一种节能的路径查找算法，可在存在障碍物的三维空间中确定最低能耗的路线。该算法基于无人机推进系统和飞行动力学对能耗进行建模。我们进行了广泛的评估，将EcoFlight与直飞方案和最短距离方案进行了比较。在不同障碍物密度下的仿真结果表明，EcoFlight始终能找到比同类算法能耗更低的路径，尤其是在高密度环境中。我们还证明，合适的飞行速度可以进一步提高节能效果。