A Modal-Space Formulation for Momentum Observer Contact Estimation and Effects of Uncertainty for Continuum Robots

TL;DR

This paper extends dynamic contact detection to continuum robots using a modal-space momentum observer, enabling real-time contact force estimation and analysis of uncertainties, validated through simulations and experiments.

Contribution

It introduces a novel modal-space momentum observer approach for contact estimation in continuum robots, including methods for wrench identification and uncertainty analysis.

Findings

Effective contact detection in continuum robots demonstrated

Comparison shows momentum observer outperforms joint force deviation method

Method extended to multisegment continuum robots

Abstract

Contact detection for continuum and soft robots has been limited in past works to statics or kinematics-based methods with assumed circular bending curvature or known bending profiles. In this paper, we adapt the generalized momentum observer contact estimation method to continuum robots. This is made possible by leveraging recent results for real-time shape sensing of continuum robots along with a modal-space representation of the robot dynamics. In addition to presenting an approach for estimating the generalized forces due to contact via a momentum observer, we present a constrained optimization method to identify the wrench imparted on the robot during contact. We also present an approach for investigating the effects of unmodeled deviations in the robot's dynamic state on the contact detection method and we validate our algorithm by simulations and experiments. We also compare the performance of the momentum observer to the joint force deviation method, a direct estimation approach using the robot's full dynamic model. We also demonstrate a basic extension of the method to multisegment continuum robots. Results presented in this work extend dynamic contact detection to the domain of continuum and soft robots and can be used to improve the safety of large-scale continuum robots for human-robot collaboration.