针对固定安装的激光雷达在大规模场景探索时效率不高的问题，提出了一种面向雷达倾角可控的无人机自主探索运动规划算法，包括轻量化的视点生成和考虑雷达倾角可控特性的路径规划。在视点生成部分，首先基于边界法向量生成视点以降低算力需求，然后根据边界与视点相对位置计算雷达倾角，以提升单视点可观测的边界单元数量。在路径规划中，考虑雷达倾角可控特性的等效视点机制，利用雷达倾角调整减少无人机偏航角调整时间，降低轨迹切换的时间成本和减少冗余移动，以缩短探索任务时间。仿真结果表明：相比FUEL方法，本文方法在典型工厂场景中的平均探索时间和路径长度减少约10%；在多层结构化的商场场景中的探索时间缩短20%以上，路径长度减少10%以上。
To address the issue of low efficiency in large-scale scene exploration when using a fixed-mount LIDAR, an autonomous exploration motion planning method with LIDAR pitch controllable for unmanned aerial vehicles (UAV) is proposed. This method consists of lightweight viewpoint generation and path planning considering characteristics of LIDAR pitch controllable. In the viewpoint generation, a frontier normal-based viewpoint generation method is employed to reduce computational load. Then, the LIDAR pitch is calculated based on the relative position between the frontier and the viewpoint, so as to increase the number of observable frontier at viewpoints. In the path planning, an equivalent viewpoint mechanism considering the characteristics of LIDAR pitch controllable enables adjustments of the LIDAR pitch to reduce UAV yaw adjustment time, which decreases the switch time of trajectory and redundant movements, thereby reducing the overall exploration task duration. Simulation results demonstrate that compared to the FUEL method, the proposed method reduces the average exploration time and path length by about10% in a typical factory scenario, and reduces over 20% exploration time and over 10% path length in a multi-story structured mall.
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