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.

翻译：许多应用要求机器人精确追踪参考末端执行器轨迹。由于机器人运动学约束或环境中其他障碍物的存在，某些轨迹可能无法作为单一连续路径被追踪。此时，需将轨迹分割为较短片段。每次分割会引入一次重配置，即机器人偏离参考轨迹，在构型空间中重新定位后继续执行任务。应尽量减少重配置次数，因其会增加时间与能量消耗。本文提出IKLink方法，通过执行最少重配置来寻找跟踪参考末端执行器轨迹的关节运动。该基于图的方法为参考轨迹上每个航点生成多样化的逆运动学解，并利用动态规划算法通过链接这些逆运动学解寻找全局最优运动。我们通过仿真实验和实际机器人演示验证了IKLink的有效性。