Iterative Reference Learning for Cartesian Impedance Control of Robot Manipulators
In this paper, an iterative learning strategy was developed to improve trajectory tracking for an impedance-controlled robot manipulator. In this learning strategy, an update law was proposed to modify the Cartesian reference of an impedance controller. Also, the conditions that ensure its convergence considering the dynamics of the robot were derived. Finally, an experimental evaluation was perfo
