IKLink: End-Effector Trajectory Tracking with Minimal Reconfigurations

Many applications require a robot to accurately track reference end-effector trajectories. Certain trajectories may not be tracked as single, continuous paths due to the robot’s kinematic constraints or obstacles elsewhere in the environment. In this situation, it becomes necessary to divide the trajectory into shorter segments. Each such division introduces a reconfiguration, in which the robot deviates from the reference trajectory, repositions itself in configuration space, and then resumes task execution. The occurrence of reconfigurations should be minimized because they increase time and energy usage. In this paper, we present IKLink, a method for finding joint motions to track reference end-effector trajectories while executing the minimum number of reconfigurations. Our graph-based method generates a diverse set of Inverse Kinematics (IK) solutions for every waypoint on the reference trajectory and utilizes a dynamic programming algorithm to find the optimal motion by linking the IK solutions. We demonstrate the effectiveness of IKLink through a simulation experiment and an illustrative demonstration using a physical robot.