An Open-Source, Reproducible Tensegrity Robot That Can Navigate Among Obstacles
William R. Johnson III, Patrick Meng, Nelson Chen, Luca Cimatti, Augustin Vercoutere, Mridul Aanjaneya, Rebecca Kramer-Bottiglio, Kostas E. Bekris
Abstract
Tensegrity robots, composed of rigid struts and elastic tendons, provide impact resistance, low mass, and adaptability to unstructured terrain. Their compliance and complex, coupled dynamics, however, present modeling and control challenges, hindering planning and obstacle avoidance. This letter presents a complete, open-source, and reproducible system that enables navigation for a 3-bar tensegrity robot. The system comprises: (i) an inexpensive, open-source hardware design, and (ii) an integrated, open-source software stack for physics-based modeling, system identification, state estimation, path planning, and control. All hardware and software are publicly available at tensegrity.yale.edu. The proposed system tracks the robot using a static overhead camera and executes collision-free paths to a goal among known obstacle locations. System robustness is demonstrated through experiments involving unmodeled environmental challenges, including a vertical drop, an incline, and granular media, culminating in an outdoor field demonstration. To validate reproducibility, experiments were conducted using robot instances at two different laboratories. This work provides the robotics community with a complete navigation system for a compliant, impact-resistant, and shape-morphing robot. This system is intended to serve as a springboard for advancing the navigation capabilities of other unconventional robotic platforms.
BibTeX
@inproceedings{ral2026_anopensourcerepr,
title = {An Open-Source, Reproducible Tensegrity Robot That Can Navigate Among Obstacles},
author = {William R. Johnson III and Patrick Meng and Nelson Chen and Luca Cimatti and Augustin Vercoutere and Mridul Aanjaneya and Rebecca Kramer-Bottiglio and Kostas E. Bekris},
booktitle = {RA-L 2026},
year = {2026}
}