Human–Robot Cooperation Control Based on Trajectory Deformation Algorithm for a Lower Limb Rehabilitation Robot
Jie Zhou, Zhijun Li, Xianming Li, Xiaoyun Wang, Rong Song
Abstract
Although many studies have certified the advantages of human–robot cooperation control with admittance model (AM), robot compliance, and movement smoothness need to be further improved. In this article, a trajectory deformation algorithm (TDA) is developed as a high-level trajectory planner, which can plan subject's desired trajectory based on interaction force during physical human–robot interaction (pHRI). A low-level proportional-derivative (PD) position controller is selected to ensure the lower limb rehabilitation robot can track the desired trajectory. Then, the validity of TDA is verified through simulation and experiment studies. The energy per unit distance (EPUD) and dimensionless squared jerk (DSJ) are chosen as indicators of robot compliance and movement smoothness, respectively. The experimental results demonstrated that both the EPUD and the DSJ values using TDA are smaller than that using the AM, indicating the TDA can improve robot compliance and movement smoothness. Therefore, it may have great potential in fields involving pHRI, such as robot-aided rehabilitation.