Applying Dynamic Movement Primitives to Motion Planning and Inverse Kinematics Problems of an Upper Limb Exoskeleton Robot

Motion planning and inverse kinematics (IK) are two important parts of controlling the robot exoskeleton. To make the wearer feel comfortable, the joints variable values need to be similar to the values measured in the actual activities of the human arm. Dynamic movement primitives (DMPs) are a useful solution to this problem. In this study, we proposed to apply DMPs to generate the robot’s end-effector position and orientation trajectory as well as the robot’s joint variable values trajectory from the actual measured joints values of the robot exoskeleton during Activity of Daily Living exercise such as reaching a cup of water. Then, with the same ADL, when changing position of end-effector, the proposed algorithm could generate the end-effector trajectory and joints’ values as well. The results showed that the end-effector position and orientation trajectory and the joints variable had the same form as the sample one. This proved that we can absolutely apply DMP to solve the Inverse Kinematics and Motion planning for robots without solving complicated inverse kinematics problems.