Online obstacle avoidance path planning and application for arc welding robot

Abstract

• The system of online collision-free path planning for the arc welding robot is established. • An improved lazy-PRM algorithm with repulsion field is proposed to solve the path planning. • The collision-free path of the 7-DOF arc welding robot can be planned online. • The path quadratic optimization strategy is proposed to fine-tuning the pose and position of the welding gun. • Fast trajectory planning for each workpiece at any position during the welding process. The offline path planning problem for arc welding robots becomes increasingly difficult to achieve with the increasing product complexity and the open work environment, such as the welding tasks in ship formation. Most research considers the path planning problem without time limitations or other constraints that conform to the actual production process. During the welding process, the placement of workpieces seriously affects the efficiency of finding feasible paths for the welding robots for weld tasks that cannot be repeated accurately. Thus, in the flow welding workshop, the improved lazy Probabilistic Roadmap (PRM) algorithm based online collision-free path planning method is proposed to finish the welding tasks of general stiffened plates at an arbitrary position on the workbench within the robot's reach. The work environment is built with the grid method to reduce the computational dimension of collision detection. The local path planner is implemented by the lazy-PRM algorithm with the repulsive force field to rapidly search the collision-free path for the welding robot with specific safe distances. The robot posture adjustment strategy is also applied to the collision detection process to adjust some poses of the robot at candidate paths to be feasible. The improved path planning method is tested on both the simulated environment and actual application scenario and proved to be suitable for the path planning problem of the arc welding robot. The results of this study have been integrated into a computer approach, which can accelerate the motion planning process and reduce human efforts.