Adaptive Preload Control of Cable-Driven Parallel Robots for Handling Task
Thomas Reichenbach, Johannes Clar, Andreas Pott, Alexander Verl
TL;DR
This work addresses the need for adjustable platform stiffness in cable-driven parallel robots to balance precision and energy efficiency during handling tasks. It proposes Adaptive Preload Control (APC), leveraging an extended nullspace formulation to compute feasible preload parameters in real time and using an invertible extended structure matrix to obtain a unique force distribution for a given wrench. The method is validated through simulation against a conventional force distribution approach and demonstrated experimentally on a COPacabana system, showing that stiffness can be increased during loading/unloading and reduced during nominal motion without compromising pose accuracy. The results highlight APC's potential to enable hybrid position-force control with adaptive cable preload, offering practical benefits for large-scale manipulation and paving the way for application to highly redundant reconfigurable cable robots.
Abstract
This paper presents a method for dynamic adjustment of cable preloads based on the actuation redundancy of \acp{CDPR}, which allows increasing or decreasing the platform stiffness depending on task requirements. This is achieved by computing preload parameters with an extended nullspace formulation of the kinematics. The method facilitates the operator's ability to specify a defined preload within the operation space. The algorithms are implemented in a real-time environment, allowing for the use of optimization in hybrid position-force control. To validate the effectiveness of this approach, a simulation study is performed, and the obtained results are compared to existing methods. Furthermore, the method is investigated experimentally and compared with the conventional position-controlled operation of a cable robot. The results demonstrate the feasibility of adaptively adjusting cable preloads during platform motion and manipulation of additional objects.
