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

2025-05-05

AI Summary

To address low contact detection accuracy and poor robustness in dynamic human–robot collaboration involving continuum and soft robots, this paper proposes a real-time contact force/torque estimation method based on modal-space dynamic modeling and a Generalized Momentum Observer (GMO). This work is the first to introduce the GMO into contact perception for continuum robots, integrating fiber-optic shape sensing to achieve high-fidelity, real-time deformation feedback and employing constrained nonlinear optimization to invert contact torques. Theoretical analysis quantifies the impact of unmodeled dynamics on estimation performance. Simulation and experimental results demonstrate significant improvements in contact location and torque estimation accuracy, enhanced disturbance rejection, and seamless scalability to multi-segment continuum configurations. Moreover, the method outperforms conventional joint-torque residual approaches on a full-dynamics benchmark. This framework establishes a reliable perceptual foundation for safe physical human–robot interaction.

Technology Category

• Intelligent Robots: State Estimation
• Search and Optimization: Mixed Discrete/Continuous Search
• Constraint Satisfaction and Optimization: Mixed Discrete/Continuous Optimization

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Economics, Online Markets and Human Computation: Trust and reliance of crowd workers and data experts on GenAI

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.

Problem

• Develops momentum observer for contact estimation in continuum robots
• Investigates effects of dynamic state uncertainty on contact detection
• Extends dynamic contact detection to multi-segment continuum robots

Innovation

• Adapts momentum observer to continuum robots
• Uses modal-space for robot dynamics representation
• Employs constrained optimization for wrench identification