Moving-Horizon Estimation and Nonlinear Model Predictive Control of Cable-Driven Soft Manipulators
2026-07-27 • Robotics
Robotics
AI summaryⓘ
The authors address the challenge of precisely controlling soft robotic arms by using a simplified physics model called the reduced Cosserat-rod. They developed a method to estimate the robot's shape and position without needing direct tension sensors on the cables, relying instead on measurements of cable lengths and the arm's end position. Their approach combines estimation and control techniques to guide the soft robot in real time while respecting cable limitations. Tested in simulations and on a physical prototype, their method showed accurate control of the robot's tip position using only cable length adjustments.
soft manipulatorsCosserat-rod modelmoving-horizon estimation (MHE)nonlinear model predictive control (NMPC)cable-driven robotsend-effectorstate estimationcomplementarity constraintmodel-based controlreal-time control
Authors
Lingxiao Xun, Haihong Li, Gang Zheng
Abstract
Precise control of soft manipulators remains challenging due to the difficulty of developing accurate yet computationally tractable models for model-based estimation and control. Reduced Cosserat-rod models provide a physics-based and control-oriented description of soft-robot dynamics, offering an explicit alternative to purely data-driven input-output representations. In this paper, we propose a moving-horizon estimation (MHE) and nonlinear model predictive control (NMPC) framework for cable-driven soft manipulators based on reduced Cosserat dynamics. A smooth cable-length-driven modeling formulation is developed by approximating the complementarity relationship between cable tension and cable slackness, enabling cable-length control without direct tension sensing. Based on this formulation, an MHE method is introduced to estimate the reduced state and reconstruct the manipulator configuration from end-effector pose measurements and cable-length information. An NMPC controller is then formulated to achieve task-space control under cable-length and cable-rate constraints. The proposed framework is validated through numerical simulations and experiments. Simulation results demonstrate the effectiveness of the estimator and controller for pose and strain-related regulation on a multi-cable soft manipulator. Experimental results on a four-cable prototype further show that the proposed MHE-NMPC scheme can be implemented in real time and enables accurate end-effector position tracking through cable-length control.