Adaptive Force Controller for Contact-Rich Robotic Systems using an Unscented Kalman Filter

TL;DR

This paper presents an adaptive force control method for contact-rich robotic systems that uses an Unscented Kalman Filter for auto-tuning, improving stability and safety during interactions.

Contribution

It introduces an auto-tuning admittance controller utilizing an Unscented Kalman Filter for real-time gain adjustment in multi-point contact robots.

Findings

Successfully applied on hardware for manipulation tasks

Enhanced stability and contact accuracy

Maintained force limits to prevent slippage

Abstract

In multi-point contact systems, precise force control is crucial for achieving stable and safe interactions between robots and their environment. Thus, we demonstrate an admittance controller with auto-tuning that can be applied for these systems. The controller's objective is to track the target wrench profiles of each contact point while considering the additional torque due to rotational friction. Our admittance controller is adaptive during online operation by using an auto-tuning method that tunes the gains of the controller while following user-specified training objectives. These objectives include facilitating controller stability, such as tracking the wrench profiles as closely as possible, ensuring control outputs are within force limits that minimize slippage, and avoiding configurations that induce kinematic singularity. We demonstrate the robustness of our controller on hardware for both manipulation and locomotion tasks using a multi-limbed climbing robot.