Path Planning for Mobile Robot Based on Angle Search
The angle search algorithm for angle-controlled robots is proposed to increase the path search speed and optimize the path length.The algorithm effectively finds a path in static surroundings by performing an efficient search in a specific dimensional range based on the position of the robot and the target point.Firstly,search angles are predetermined according to the characteristics of the environment in the grid map.Then,the estimated angle of the robot's surrounding grid is computed.Finally,a new extension point is chosen by comparing the estimated angle to the search angle,demonstrating the usefulness and viability of the suggested algorithm.The proposed algorithm is compared with the Dijkstra and A*algorithms on two types of maps with different levels of complexity.The path finding time of the proposed algorithm is reduced by 19.44％and 12.23％respectively,and the number of turns is reduced by 28.6％and 54.5％respectively.The path length is reduced by 9.28％and 6.53％respectively compared with the A*algorithm on the two maps,and the dynamic avoidance of local obstacles is realized in simple scenes.The proposed algorithm is then applied to the ROS-based Turtlebot2 mobile robot,and the experimental results reveal that it is smoother and more stable than the A*algorithm in the same map environment,proving its viability and effectiveness.
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