Research on path planning optimization of inspection robot in multi-obstacle environment
In the case of the large-scale and dense obstacle distributions,it is a challenge to search the best path efficiently.In order to get shorter inspection routes and achieve flexible obstacle avoidance in multi-obstacle environments,a research on path planning optimization methods for inspection robots in multi-obstacle environments is carried out.An inspection environment model is constructed by a two-dimensional matrix.The D* algorithm is applied to plan the path of the inspection robot in the inspection environment model.The means of the extended step size in the traditional D* algorithm is changed to adaptive extended step size,so that the robot can complete inspections faster in larger inspection sites.The cost function is replaced by the one based on the fusion of Chebyshev distance and Manhattan distance.The smoothness function is introduced to optimize the route planning results,which makes the planned path smoother and can be re-planned when encountering new obstacles due to various reasons.It can be concluded with experimental results that the proposed method can plan the optimal route for both static and dynamic maps quickly and accurately,and its application in various environments can obtain path planning results efficiently.
万方数据
维普
