基于多传感器的无人机避障方法研究及应用

随着无人机巡检作业方式应用越来越广泛,巡检过程中对障碍物检测并进行避障显得愈发关键。若无人机碰到杆塔或线路不仅会造成无人机自身的损坏,还会对居民用电造成影响,给检修带来麻烦。毫米波雷达、激光雷达、双目视觉传感器在机器人避障中有广泛应用。但是基于输电线路巡检的多旋翼无人机的实际情况,传感器器件的选型、尺寸、重量,以及障碍物信息与飞控的融合,显得尤为重要。通过对多旋翼无人机搭载毫米波雷达、双目视觉传感器、差分GPS进行了研究,采用多传感器融合方法检测障碍物,利用虚拟力场法(VFF)进行航迹重规划,并实际飞行验证。测试表明该方法对杆塔避障取得了较好的应用效果。

Research and Application of Obstacle Avoidance Method Based on Multi-sensor for UAV

With the wider application of unmanned aerial vehicle (UAV) inspection methods, obstacle detection and avoidance are becoming more and more important. If the UAV hits a tower or a line, it will not only cause its own damage, but also affect the electricity consumption of the residents, and also cause troubles for maintenance. Millimeter-wave radar, laser radar, and binocular stereo vision sensors are widely used in robot obstacle avoidance. But based on the actual conditions of multi-rotor UAVs for transmission line inspection, the model selection, size, weight, the integration of obstacle information and flight control are particularly important. The multi-rotor UAV equipped with millimeter-wave radar and binocular stereo vision and Differential GPS were studied. Multi-sensor fusion method was used to detect obstacles, and virtual force field method (VFF) was used for track replanning, and conducting a flight test. The test result shows that this method has a good application effect on obstacle avoidance of towers.