Scalable Open-Source Visuotactile Sensor for 6-Axis Contact Wrench Estimation in Tensegrity Robots

2026-07-17

AI Summary

This work addresses the lack of low-cost, scalable six-degree-of-freedom (6-DoF) tactile sensing in tensegrity robots by proposing an open-source vision-based tactile sensor. The design features a glue-free, gyroid-infused architecture that robustly bonds an elastomer with thermoplastic polyurethane (TPU), integrated with a 3D-printed TPU interface, an embedded camera, and ring LED illumination, achieving lightweight, modular, and manufacturable characteristics. A neural network maps shear vector fields—induced by shell deformation—to 6-DoF force/torque estimates, yielding a low mean squared error of 0.1531 in static tests. The system demonstrates dynamic out-of-distribution generalization and enables reliable ground contact detection on a 12-kg tensegrity robot, facilitating physically interpretable proprioceptive tactile perception.

Abstract

This paper presents a scalable, open-source visuotactile sensing system for tensegrity robots that enables six-axis wrench estimation and contact detection. The proposed endcap sensor integrates an elastomeric shell, a 3D-printed thermoplastic polyurethane (TPU) interface, and a rigid base housing an embedded camera and LED illumination ring. A novel gyroid-infill bonding technique is introduced to form a durable elastomer-TPU interface without adhesives, yielding a lightweight and modular design compatible with large-scale tensegrity structures. A tactile-to-wrench neural network maps shear vector fields to six-dimensional force and torque measurements. Experimental results demonstrate accurate and stable wrench estimation with a mean squared error (MSE) of 0.1531 on static validation data and out-of-domain generalization under dynamic motion. Furthermore, full-system integration on a 12 kg tensegrity robot confirms the sensor's ability to reliably identify ground contacts. The system substantially improves the practicality of tactile feedback for tensegrity robots, offering a low-cost, reproducible, and physically interpretable pathway toward contact-aware proprioception and state estimation. Open source files are available at \href{https://github.com/Jonathan-Twz/tensegrity-gelfoot}{github.com/Jonathan-Twz/tensegrity-gelfoot}

Problem

• visuotactile sensing
• 6-axis wrench estimation
• tensegrity robots
• contact detection
• scalable tactile sensor

Innovation

• visuotactile sensing
• 6-axis wrench estimation
• tensegrity robots
• gyroid-infill bonding
• tactile-to-wrench neural network