A Control Framework Definition to Overcome Position/Interaction Dynamics Uncertainties in Force-Controlled Tasks
Loris Roveda, Nicola Castaman, Paolo Franceschi, Stefano Ghidoni, Nicola Pedrocchi
Abstract
Within the Industry 4.0 context, industrial robots need to show increasing autonomy. The manipulator has to be able to react to uncertainties/changes in the working environment, displaying a robust behavior. In this paper, a control framework is proposed to perform industrial interaction tasks in uncertain working scenes. The proposed methodology relies on two components: i) a 6D pose estimation algorithm aiming to recognize large and featureless parts; ii) a variable damping impedance controller (inner loop) enhanced by an adaptive saturation PI (outer loop) for high accuracy force control (i.e., zero steady-state force error and force overshoots avoidance). The proposed methodology allows to be robust w.r.t. task uncertainties (i.e. , positioning errors and interaction dynamics). The proposed approach has been evaluated in an assembly task of a side-wall panel to be installed inside the aircraft cabin. As a test platform, the KUKA iiwa 14 R820 has been used together with the Microsoft Kinect 2.0 as RGB-D sensor. Experiments show the reliability in the 6D pose estimation and the high-performance in the force-tracking task, avoiding force overshoots while achieving the tracking of the reference force.