The demand is to solve the issue of UAV (unmanned aerial vehicle) operating
autonomously and implementing practical functions such as search and rescue in
complex unknown environments. This paper proposes an autonomous search and
rescue UAV system based on an EGO-Planner algorithm, which is improved by
innovative UAV body application and takes the methods of inverse motor
backstepping to enhance the overall flight efficiency of the UAV and
miniaturization of the whole machine. At the same time, the system introduced
the EGO-Planner planning tool, which is optimized by a bidirectional A*
algorithm along with an object detection algorithm. It solves the issue of
intelligent obstacle avoidance and search and rescue. Through the simulation
and field verification work, and compared with traditional algorithms, this
method shows more efficiency and reliability in the task. In addition, due to
the existing algorithm's improved robustness, this application shows good
prospection.

该论文提出了一种基于 EGO-Planner 算法的自主搜索与救援无人机系统，通过创新的无人机应用和逆向电机反馈算法来提高无人机的飞行效率和整机微型化，并通过引入 EGO-Planner 规划工具和双向 A * 算法以及目标检测算法解决了智能避障和搜索救援的问题，经过仿真和实地验证，并与传统算法进行比较，该方法在任务中展现出更高的效率和可靠性，同时由于改进的稳健性，这一应用有很好的前景。