Logo
ScienceStack
Table of Contents
Fetching ...
Sign In

Control the Soft Robot Arm with its Physical Twin

Qinghua Guan, Hung Hon Cheng, Benhui Dai, Josie Hughes

TL;DR

The paper introduces Physical Twin Control (PTC), a teleoperation framework for soft tendon-driven arms that uses an identical physical twin as the demonstrator to capture full-body deformation via tendon-length sensing. It enables direct 1:1 or 1:X mappings to a soft executor, balancing back-drivable admittance control with proprioception and tunable friction/stiffness across arm segments. Experimental results demonstrate faithful motion transfer, configuration-aware mapping under varying stiffness distributions, and practical tasks such as narrow-gap navigation and workspace expansion with a scaled-up executor. The work suggests that physical-twin-based teleoperation reduces reliance on complex models and enables intuitive control of compliant soft robots, with future work extending autonomy and multimodal feedback.

Abstract

To exploit the compliant capabilities of soft robot arms we require controller which can exploit their physical capabilities. Teleoperation, leveraging a human in the loop, is a key step towards achieving more complex control strategies. Whilst teleoperation is widely used for rigid robots, for soft robots we require teleoperation methods where the configuration of the whole body is considered. We propose a method of using an identical 'physical twin', or demonstrator of the robot. This tendon robot can be back-driven, with the tendon lengths providing configuration perception, and enabling a direct mapping of tendon lengths for the execture. We demonstrate how this teleoperation across the entire configuration of the robot enables complex interactions with exploit the envrionment, such as squeezing into gaps. We also show how this method can generalize to robots which are a larger scale that the physical twin, and how, tuneability of the stiffness properties of the physical twin simplify its use.

Control the Soft Robot Arm with its Physical Twin

TL;DR

The paper introduces Physical Twin Control (PTC), a teleoperation framework for soft tendon-driven arms that uses an identical physical twin as the demonstrator to capture full-body deformation via tendon-length sensing. It enables direct 1:1 or 1:X mappings to a soft executor, balancing back-drivable admittance control with proprioception and tunable friction/stiffness across arm segments. Experimental results demonstrate faithful motion transfer, configuration-aware mapping under varying stiffness distributions, and practical tasks such as narrow-gap navigation and workspace expansion with a scaled-up executor. The work suggests that physical-twin-based teleoperation reduces reliance on complex models and enables intuitive control of compliant soft robots, with future work extending autonomy and multimodal feedback.

Abstract

To exploit the compliant capabilities of soft robot arms we require controller which can exploit their physical capabilities. Teleoperation, leveraging a human in the loop, is a key step towards achieving more complex control strategies. Whilst teleoperation is widely used for rigid robots, for soft robots we require teleoperation methods where the configuration of the whole body is considered. We propose a method of using an identical 'physical twin', or demonstrator of the robot. This tendon robot can be back-driven, with the tendon lengths providing configuration perception, and enabling a direct mapping of tendon lengths for the execture. We demonstrate how this teleoperation across the entire configuration of the robot enables complex interactions with exploit the envrionment, such as squeezing into gaps. We also show how this method can generalize to robots which are a larger scale that the physical twin, and how, tuneability of the stiffness properties of the physical twin simplify its use.

Paper Structure

This paper contains 15 sections, 6 equations, 9 figures, 2 tables.

Table of Contents

  1. Introduction
  2. Methods
  3. Soft Robot Design
  4. Demonstrator Arm Control: Back-drivable Admittance Control with Proprioception
  5. Mapping to Executer Robot
  6. Executer Robot Arm Control: Active friction and stiffness control
  7. Experimental Setup
  8. Experimental Results
  9. Motion Mapping Between the Twin Arms
  10. Directional Error of the Mapping
  11. Human-robot Interactions Under Different Stiffness Distributions
  12. Demonstration of Teleoperation
  13. Navigation Through a Narrow Gap
  14. Workspace Expansion with a Scaled-Up Twin
  15. Conclusion and Discussion

Figures (9)

  • Figure 1: a) Teleoperation of a soft arm leveraging a physical twin to achieve implicit configuration perception and direct mapping, b) The capabilities and uses of this teleoperation method, and c) The ability to map from demonstrator to robots of different scales (i.e. a 1:X scale mapping)
  • Figure 2: Soft twin arm Design and mechanism
  • Figure 3: Influence of Friction and Stiffness Regulation on Deformation Response. (a) Initial Deformation Under External Load. (b) Experimental Setup for Load Application. (c) Effect of Friction Distribution (LLL vs. HHH). (d) Effect of Friction Distribution (LHH vs. HLL). (e) Effect of Stiffness Variation (LLL vs. HHH). (f) Localized Stiffness Regulation (LHH vs. HLL).
  • Figure 4: Experimental Setup for teleportation and data collection of twin arm
  • Figure 5: Teleoperationed trajectories of the Demonstrator and Executor Arms. (a) Circular trajectory, (b) Square trajectory, (c) Triangular trajectory, (d) Five-pointed star trajectory.
  • ...and 4 more figures