3D Shape Control of Extensible Multi-Section Soft Continuum Robots via Visual Servoing

2026-02-22

AI Summary

This work addresses the limitation of existing visual servoing methods for soft continuum robots, which typically regulate only the end-effector pose and fail to exploit kinematic redundancy for full-body shape control. The authors propose a novel 2.5D shape servoing algorithm based on external monocular vision that achieves precise three-dimensional whole-body shape regulation without requiring onboard sensors. By integrating model-driven full-body shape estimation with inverse kinematics to generate reference features, the method eliminates dependence on reference images and ensures globally asymptotically stable convergence, thereby avoiding local minima. Experimental results demonstrate a steady-state error below 1 mm, smooth transient responses, and successful execution of complex manipulation tasks—including stacking, pouring, and pulling—validating the effectiveness and practicality of the proposed approach.

Technology Category

• Intelligent Robots: Manipulation
• Computer Vision: Low Level & Physics-based Vision
• Planning, Routing, and Scheduling: Mixed Discrete/Continuous Planning

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

In this paper, we propose a novel vision-based control algorithm for regulating the whole body shape of extensible multisection soft continuum manipulators. Contrary to existing vision-based control algorithms in the literature that regulate the robot's end effector pose, our proposed control algorithm regulates the robot's whole body configuration, enabling us to leverage its kinematic redundancy. Additionally, our model-based 2.5D shape visual servoing provides globally stable asymptotic convergence in the robot's 3D workspace compared to the closest works in the literature that report local minima. Unlike existing visual servoing algorithms in the literature, our approach does not require information from proprioceptive sensors, making it suitable for continuum manipulators without such capabilities. Instead, robot state is estimated from images acquired by an external camera that observes the robot's whole body shape and is also utilized to close the shape control loop. Traditionally, visual servoing schemes require an image of the robot at its reference pose to generate the reference features. In this work, we utilize an inverse kinematics solver to generate reference features for the desired robot configuration and do not require images of the robot at the reference. Experiments are performed on a multisection continuum manipulator demonstrating the controller's capability to regulate the robot's whole body shape while precisely positioning the robot's end effector. Results validate our controller's ability to regulate the shape of continuum robots while demonstrating a smooth transient response and a steady-state error within 1 mm. Proof-of-concept object manipulation experiments including stacking, pouring, and pulling tasks are performed to demonstrate our controller's applicability.

Problem

• soft continuum robots
• 3D shape control
• visual servoing
• whole-body shape regulation
• extensible manipulators

Innovation

• visual servoing
• soft continuum robots
• 3D shape control
• kinematic redundancy
• model-based control