Efficient online motion planning method for the robotic arm to pick-up moving objects smoothly with temporal constraints

Abstract

This paper proposes a new efficient online motion planning method for the manipulator to grasp moving objects smoothly. The algorithm framework consists of front-end pathfinding and back-end nonlinear trajectory optimization. The sample-based pathfinding algorithm can predict the intersection location and find a safe initial path in the dynamic environment. The gradient-based continuous-time trajectory optimization method converts the Euclidean Signed Distance Field information into the joint space, uses the B-spline curve to represent the joint trajectories, optimizes the initial path using convex hull characteristics of B-spline, and generates a smooth and kinematics feasible trajectory in joint space. Finally, we use an adjustment method of iterative trajectory fragment length to guarantee kinodynamic feasibility. Simulation comparisons and real-world experiments verify our planning framework’s high performance.