To avoid obstacle in the unknown environment for unmanned undersea vehicle (UUV), an obstacle avoiding system based on improved vector field histogram (VFH) is designed. Forward looking sonar is used to detect the environment, and the divisional sonar modal is applied to deal with the measure uncertainty. To adapt to the VFH, rolling occupancy grids are used for the map building, and high accuracy details of local environment are obtained. The threshold is adaptively adjusted by the statistic of obstacles to solve the problem that VFH is sensitive to threshold. To improve the environment adaptability, the hybrid-behaviors strategy is proposed, which selects the optimal avoidance command according to the motion status and environment character. The simulation shows that UUV could avoid the obstacles fast and escape from the U shape obstacles.
Wavelet Occupancy Grids: A Method for Compact Map Building