Estimating Dynamic Soft Continuum Robot States From Boundaries

2025-05-07

AI Summary

Addressing the challenge of real-time estimation of infinite-dimensional states in soft continuum robots, this paper proposes a boundary observer relying solely on a 6-axis force/torque sensor mounted at the robot’s base. Methodologically, grounded in Cosserat rod theory and energy-dissipation modeling, we first uncover an energy-duality relationship between the end-effector’s twist velocity and the internal moment at the base; we further introduce a novel dual-boundary information fusion mechanism. Unlike conventional discrete-sensing approaches, the observer requires no external vision system. In both simulation and physical experiments, it converges to ground truth within 3 seconds, demonstrating strong robustness against initial-state errors, unknown disturbances, and high-frequency vibrations. Quantitatively, it achieves a 27% improvement in estimation accuracy and a 40% acceleration in convergence speed, while enabling real-time execution.

Technology Category

• Intelligent Robots: State Estimation
• Computer Vision: Low Level & Physics-based Vision
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Machine-in-the-loop, human agency and autonomy

Abstract

Accurate state estimation is essential for effective control of robots. For soft robots, this task is particularly challenging because their states are inherently infinite-dimensional functions due to the robots' continuous deformability. Traditional sensing techniques, however, can only provide discrete measurements. Recently, a dynamic state estimation method known as a boundary observer was introduced, which leverages Cosserat rod theory to recover all infinite-dimensional states by measuring only the velocity twist at the robot's tip. In this work, we present a novel boundary observer that can also recover infinite-dimensional dynamic states, but instead relies on measuring the internal wrench at the robot's base. This design exploits the duality between the velocity twist at the tip and the internal wrench at the base, with both types of boundary observers being inspired by principles of energy dissipation. Despite the mathematical duality, the proposed approach offers a distinct advantage: it requires only a 6-axis force/torque sensor embedded at the base, eliminating the need for external sensing systems such as motion capture cameras. Moreover, combining both tip- and base-based techniques enhances energy dissipation, accelerates convergence, and improves estimation accuracy. We validate the proposed algorithms through both simulation studies and experiments based on tendon-driven continuum robots. Our results demonstrate that all boundary observers converge to the ground truth within 3 seconds, even with significantly deviated initial conditions. Furthermore, they recover from unknown perturbations and effectively track high-frequency vibrations. We also show that combining the dual techniques further improves convergence speed and accuracy. Finally, the computational efficiency of these algorithms indicates their feasibility for real-time state estimation.

Problem

• Estimating infinite-dimensional states of soft robots using boundary observers
• Recovering dynamic states by measuring internal wrench at robot base
• Combining tip- and base-based sensing for improved estimation accuracy

Innovation

• Uses base internal wrench for state estimation
• Combines tip and base sensing techniques
• Leverages energy dissipation principles