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

arXiv · 2511.05798

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

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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 path planning and obstacle avoidance. This paper 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 https://sites.google.com/view/tensegrity-navigation/. The proposed system tracks the robot's pose and executes collision-free paths to a specified 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.

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William R. Johnson III, Patrick Meng, Nelson Chen, Luca Cimatti, Augustin Vercoutere, Mridul Aanjaneya, Rebecca Kramer-Bottiglio, Kostas E. Bekris. 2025-11-08. An Open-Source, Reproducible Tensegrity Robot that can Navigate Among Obstacles. https://arxiv.org/abs/2511.05798

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