Advancements in Upper Body Exoskeleton: Implementing Active Gravity Compensation with a Feedforward Controller
This work addresses the need for lightweight and simplified hardware in exoskeletons for rehabilitation or assistance, though it appears incremental as it builds on existing control methods.
The study tackled the problem of active gravity compensation in upper body exoskeletons by implementing a feedforward control system that uses only positional data from motor sensors, resulting in stable performance with minimal friction and no undesired slewing in tests.
In this study, we present a feedforward control system designed for active gravity compensation on an upper body exoskeleton. The system utilizes only positional data from internal motor sensors to calculate torque, employing analytical control equations based on Newton-Euler Inverse Dynamics. Compared to feedback control systems, the feedforward approach offers several advantages. It eliminates the need for external torque sensors, resulting in reduced hardware complexity and weight. Moreover, the feedforward control exhibits a more proactive response, leading to enhanced performance. The exoskeleton used in the experiments is lightweight and comprises 4 Degrees of Freedom, closely mimicking human upper body kinematics and three-dimensional range of motion. We conducted tests on both hardware and simulations of the exoskeleton, demonstrating stable performance. The system maintained its position over an extended period, exhibiting minimal friction and avoiding undesired slewing.