Experimental Validation of Sensitivity-Aware Trajectory Planning for a Redundant Robotic Manipulator Under Payload Uncertainty
Year: 2024
Type: article
Abstract: In this letter, we experimentally validate the recent concepts ofclosed-loop state and input sensitivityin the context of robust manipulation control for a robot manipulator. Our objective is to assess how optimizing trajectories with respect to sensitivity metrics can enhance the closed-loop system's performance w.r.t. model uncertainties, such as those arising from payload variations during precise manipulation tasks. We conduct a series of experiments to validate our optimization approach across different trajectories, focusing primarily on evaluating the precision of the manipulator's end-effector at critical moments where high accuracy is essential. Our findings offer valuable insights into improving the closed-loop robustness of the robot's state and inputs against physical parametric uncertainties that could otherwise degrade the system's performance.
Authors: Ali Srour, Antonio Franchi, Paolo Robuffo Giordano, Marco Cognetti
Institutions: Centre National de la Recherche Scientifique, Institut national de recherche en sciences et technologies du numérique, Institut de Recherche en Informatique et Systèmes Aléatoires, RAINBOW: robotique interactive et référencée capteurs, Université de Rennes, University of Twente, Université Toulouse III - Paul Sabatier, Laboratoire d'Analyse et d'Architecture des Systèmes, Université de Toulouse
Language: English
Subfield: Control and Systems Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
Funder: Agence Nationale de la Recherche
OpenAlex ID: W4405520903