Skip to content
Preprint

Collocated Shape Regulation for Soft Robots

Sep 2026 · 0 citations · 43 references
Computer Science Engineering

Abstract

Controlling the shape of a continuum soft robot typically requires an accurate dynamic model and actuation of all degrees of freedom. We show that regulating only the actuated coordinates, through collocated shape control, achieves provably stable convergence of those coordinates and, under an explicit compatibility condition, of the entire robot shape. While collocated control is a cornerstone of high-performance motion control in rigid robotics, extending this formulation to continuum soft robots has remained challenging due to the complexity of their dynamics. We present the first general framework for collocated control of continuum soft robots and derive a unified family of controllers, including PD, PID, PsatID, and their counterparts with compensation and cancellation components. The framework unifies existing approaches while introducing new controller designs. In particular, we develop three classes of PD and PID like regulators with local, semi-global, and global stability guarantees, and provide rigorous convergence analyses for each. Extensive experimental validation demonstrates the effectiveness of the proposed methods across different model discretizations and controller parameters. The resulting framework provides practical design guidelines for selecting and implementing controllers with known stability guarantees, without requiring a complete dynamic model of the robot

View source

Similar papers

Open access Aug 2026

Dynamic Modeling and Real-Time Control of Continuum Soft Robots

Continuum soft robots have attracted significant attention due to their high flexibility, compliance, and ability to perform complex tasks in unstructured environments. However, their inherent nonlinear, distributed-parameter dynamics pose major challenges for accurate modeling and real-time control. Existing approache...

R. Hasan, Munif Ahmed Abdullah, Mehdi Qahraman Fakhruldin et al. · 0 citations
Conference Open access 2026

High Dimensional Modeling and Motion Control Technology for Soft Robotic

This paper analyzes in detail the principles, advantages and limitations of four core control methods based on motion models, machine learning, morphological computation and sensor feedback, and point out the key technical difficulties such as underactuated system dynamics, nonlinear hysteresis effect and flexible sens...

Zerun Song · 0 citations
Aug 2026

Spheres in motion: Adaptive dynamic programming for robotic intelligence

The potential of the proposed Adaptive Dynamic Programming (ADP) framework for improving trajectory-tracking performance in spherical robots under uncertain operating conditions is demonstrated.

Hadi Sazgar, Ali Keymasi‐Khalaji, Aliakbar Ghasemzadeh · 0 citations

Neural-Augmented Torque Control for Robotic Manipulators: Modeling, Learning, and Real-Time Performance

This thesis investigates advanced modeling and control strategies for robotic manipulators, focusing on the DLR-HIT II robotic hand and the KUKA LBR iiwa. It presents three core contributions that integrate simulation, model-based control, and data-driven methods to improve torque and position control under uncertainti...

Ali Al-Shahrabi · 0 citations
Preprint Sep 2026

On Global Regulatability of Robot Manipulators by Classical PID

A long-standing open problem in robot manipulator control is whether global regulation can be achieved by classical PID control. This paper provides an answer to this question for classical PID controllers with triple parameters (k_p,k_i,k_d) in R^3. We find and prove that for one-degree-of-freedom manipulators, the cl...

Cheng Zhao, Jing Zhu, Lei Guo · 0 citations
Preprint Aug 2026

Task-space model-based control of pneumatic soft actuators

Soft actuators enable dexterous and compliant interaction, but closed-loop task-space control remains challenging due to strong nonlinearities, distributed deformation, and uncertainty in their dynamics. This paper presents a real-time dynamic-model-based task-space feedback and estimation framework based on a non-mini...

Nithin S. Kumar, Joshua Gaston, D. C. Rucker et al. · 0 citations

We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.