This paper proposes an improved RRT*-Connect algorithm (IRRT*-Connect) for robotic arm path planning in narrow environments with multiple obstacles.A heuristic 2000 bmw 528i front bumper sampling strategy is adopted with the integration of the ellipsoidal subset sampling and goal-biased sampling strategies, which can continuously compress the sampling space to enhance the sampling efficiency.During the node expansion process, an adaptive step-size method is introduced to dynamically adjust the step size based on the obstacle information, while a node rejection strategy is used to accelerate the search process so as to generate a near-optimal collision-free path.
A pruning optimization strategy is also proposed to eliminate the redundant nodes from the path.Furthermore, a cubic non-uniform B-spline interpolation algorithm is applied to smooth the generated path.Finally, simulation experiments of the IRRT*-Connect algorithm are conducted in Python and ROS, french wrap plus and physical experiments are performed on a UR5 robotic arm.
By comparing with the existing algorithms, it is demonstrated that the proposed method can achieve shorter planning times and lower path costs of the manipulator operation.