基于障碍物分布直方图，实现微型无人机实时避障。
Histo-Planner: A Real-time Local Planner for MAVs Teleoperation based on Histogram of Obstacle Distribution
- 用障碍物分布直方图替代全局地图进行实时路径规划。
- 在仿真与室内实验中均实现稳定避障，响应延迟低。
- 适合计算资源受限的远程操控场景，如救援或巡检。
本文研究微小型飞行器（MAVs）在复杂环境中的实时避障问题。针对计算资源有限的远程操控场景，提出一种无需全局障碍物地图知识或构建的局部规划方法。该方案包含基于障碍物分布直方图的实时轨迹规划算法，以及根据周围障碍物位置动态切换规划模式的规划管理器。通过设计的仿真平台与真实室内实验，验证了方法在远程操控应用中的有效性，并进行了基准对比测试。
原文摘要 · Abstract (English)
This paper concerns real-time obstacle avoidance for micro aerial vehicles (MAVs). Motivated by teleoperation applications in cluttered environments with limited computational power, we propose a local planner that does not require the knowledge or construction of a global map of the obstacles. The proposed solution consists of a real-time trajectory planning algorithm that relies on the histogram of obstacle distribution and a planner manager that triggers different planning modes depending on obstacles location around the MAV. The proposed solution is validated, for a teleoperation application, with both simulations and indoor experiments. Benchmark comparisons based on a designed simulation platform are also provided.
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