Position estimation and object collision detection of a tendon-driven actuator based on a polytopic observer synthesis

This paper proposes a multi-model based approach that estimates joint position and collision detection of a lightweight electric actuator dedicated to manipulation tasks. Taking advantage of an optimized back-drivable mechatronic design, the use of proprioceptive measures at the motor level enables the estimation of the unmeasured terminal position of the mechanical motor-to-joint transmission and force contact disturbance. A polytopic formulation is introduced based on an accurate model of the mechatronic transmission. Then, a multi-model observer-based estimator is synthesized using root-clustering for exteroceptive variables estimation without additional position/force sensor. The approach is experimentally validated with a single degree-of-freedom manipulator.