Path Planning for Manipulators of Automotive Welding Unit Based on an Improved RRT* Algorithm

An automotive welding unit is a modular production cell within a welding workshop that integrates industrial manipulators, welding equipment, fixtures, and control systems to perform specific welding and assembly tasks. A large number of industrial manipulators are utilized in the automotive welding unit. The capability to quickly plan a short and collision-free path in the workspace of the manipulator is of great importance for improving the manipulator’s intelligence level and production efficiency. The RRT* algorithm, based on random sampling, has been widely applied in path planning for high-dimensional manipulators due to its probabilistic completeness and powerful exploration capabilities. However, the RRT* algorithm performs poorly in spaces containing narrow passages. Research on the practical application of path planning for 6-DOF manipulators is still insufficient, particularly in planning posture. To solve these two problems, an improved RRT* algorithm is proposed in this paper. New sampling and node connection strategies are designed to improve the expansion and convergence speed of the random tree in spaces containing narrow passages. A distance-constrained posture quaternion interpolation method is presented to generate smooth and continuous paths for manipulators of the automotive welding unit. Simulations and experiments are carried out to validate the proposed method, which confirms that the method can plan collision-free paths for manipulators more quickly compared to other methods.