Singularity-Avoidance Control of Robotic Systems with Model Mismatch and Actuator Constraints

arXiv (Cornell University)

Abstract

Singularities, manifesting as special configuration states, deteriorate robot performance and may even lead to a loss of control over the system. This paper addresses the kinematic singularity concerns in robotic systems with model mismatch and actuator constraints through control barrier functions (CBFs). We propose a learning-based control strategy to prevent robots entering singularity regions. More precisely, we leverage Gaussian process (GP) regression to learn the unknown model mismatch, where the prediction error is restricted by a deterministic bound. Moreover, we offer the criteria for parameter selection to ensure the feasibility of CBFs subject to actuator constraints. The proposed approach is validated by high-fidelity simulations on a 2 degrees-of-freedom (DoFs) planar robot.

Authors 3

1. Mingkun Wu Aachen Institute of Mech- anism Theory

   RWTH Aachen University · ZHAW Zurich University of Applied Sciences

   Affiliation as printed

   Institute of Mech- anism Theory, Machine Dynamics and Robotics , RWTH Aachen Uni- versity , Aachen 52062 , Germany

   ZHAW Centre for Artificial Intelligence , ZHAW Zürich University of Applied Sciences , Winterthur 8401 , Switzerland

2. Alisa Rupenyan Aachen Institute of Mech- anism Theory

   RWTH Aachen University

   Affiliation as printed

   Institute of Mech- anism Theory, Machine Dynamics and Robotics , RWTH Aachen Uni- versity , Aachen 52062 , Germany

3. Burkhard J. Corves Aachen Institute of Mech- anism Theory

   RWTH Aachen University

   Affiliation as printed

   Institute of Mech- anism Theory, Machine Dynamics and Robotics , RWTH Aachen Uni- versity , Aachen 52062 , Germany