Kinematic Redundancy Analysis during Goal-Directed Motion for Trajectory Planning of an Upper-Limb Exoskeleton Robot

Abstract

The kinematic redundancy of human arm imposes challenges on joint space trajectory planning for upper-limb rehabilitation robot. This paper aims to investigate normal motion patterns in reaching and reach-to-grasp movements, and obtain the unique solution in joint space for a five-DOF exoskeleton. Firstly, a six-camera optical motion tracking system was used to capture participants' arm motion during goal-directed reaching or reach-to-grasp movements. Secondly, statistical analysis was executed to explore the characteristics of swivel angle, which revealed that the swivel angle can be approximated to the mean value (155° ± 5°) in resolving the arm redundancy problem. Thirdly, combined with the minimum-jerk trajectory of end-effector, the generated joint trajectory complied well with the joint trajectory captured in healthy humans. Consequently, the obtained results facilitate a new way for three-dimensional trajectory planning of the exoskeleton robot. Further, adaptive assist-as-needed control of the exoskeleton robot can be implemented based on the optimal reference trajectory, with aims to provide assistance according to the patient's performance, and in turn promote neural plasticity.