Self-Adjusting Angular Resolution-based Obstacle Avoidance for Inspection Unmanned Aerial Vehicles in Nuclear Power Stations

During performing low-altitude inspection tasks in nuclear power stations, the obstacle avoidance of the UAV (Unmanned Aerial Vehicles) is a key and essential issue. To this end, a self-adjusting angular resolution algorithm is developed to improve the classical Vector Field Histogram (VFH) method. The algorithm is capable of taking advantage of the surrounding environment information and the physical motion characteristics of the UAV. The number of search sectors will automatically change according to the distribution of obstacles. On this basis, the motion step size is adjusted correspondingly, and an integrated filter is employed to reduce invalid path jitter. The simulation results prove that the self-adjusting algorithm improves the path searching speed and reduces the missed inspection of the obstacle free region. In several typical obstructed scenarios, the UAV can always reach the target position without collision, which demonstrates the superiority of developed algorithm.