IKLink: End-Effector Trajectory Tracking with Minimal Reconfigurations
CoRR(2024)
摘要
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 the time and energy
usage. In this paper, we present IKLink, a method for finding joint motions to
track reference end-effector trajectories while executing minimal
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 globally 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.
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