Obstacle avoidance path planning of a dual⁃arm inspection robot based on an improved Lazy-PRM algorithm

ObjectiveAiming at the problems of path redundancy, motion conflict, poor obstacle avoidance ability and low coordination in the path planning of dual-arm inspection robots, an obstacle avoidance path planning method based on an improved lazy probabilistic roadmap (Lazy-PRM) algorithm was proposed to enhance the operational reliability of robots in complex environments.MethodsFirstly, the improved Denavit-Hartenberg (D-H) method and grid method were adopted to construct the kinematics model of the dual manipulators and the 3D voxel environment model of the workspace, providing a foundation for path planning. Secondly, attitude preferences for different manipulators were set to assist the selection of inverse kinematics solutions and ensure trajectory smoothness. Then, a roadmap was constructed by pseudo-random sampling points, and potential optimal paths were screened using a distributed evaluation function. Finally, collision detection was conducted to verify path feasibility, and quintic polynomial interpolation was used to optimize trajectory smoothness.ResultsSimulation and test results show that the path planned by the improved algorithm is the shortest (1 737.68 mm), which is 5.2% shorter than that of the RRT* algorithm and 20.5% shorter than that of the traditional Lazy-PRM algorithm; the manipulability reaches 0.218 6, which is superior to the comparison algorithms. No motion conflict occurs between the dual manipulators, and the roadmap can be reused, providing a reference for efficient obstacle avoidance path planning of dual-arm inspection robots.