Abstract:

Aiming at the problem that dynamic obstacle avoidance algorithms for indoor mobile robots are prone to local dead zones,an improved vector field histogram(VFH) dynamic obstacle avoidance algorithm is proposed.First,according to traditional VFH-class algorithms,a path lenght cost and an evaluation index of trough width are introduced to the candidate evaluation function of the trough to reduce the probability of the mobile robot falling into local dead zones and to improve path smoothness.Second,in view of the problem that local obstacle avoidance algorithms are limited to local environment and oscillate back and forth near obstacles easily,an oscillation evaluation function is introduced with an oscillation evaluation curve drawn by calculating the weighted Euclidean distances from the pose of the mobile robot to the starting and ending points.Automatic peak detection and a first-order forward difference curve are employed to obtain the oscillation positions,and then the oscillation suppression is taken to make the mobile robot escape the local dead zones.Simulation results show that within 100 groups of simulation scenarios,the number of scenarios wherein the improved VFH algorithm falls into the local dead zones is reduced by 70 groups,the average number of planning iterations is decreased by 32.3 times,the average path length is reduced by 26.2%,and the average cumulative turning angle is declined by 79.6%.The algorithm can effectively reduce the cost of the local obstacle avoidance,improve the path smoothness and reduce the probability of falling into the dead zones in local special environment.

Key words: obstacle avoidance, VFH, local dead zone, oscillation curve