An Open-Source, Reproducible Tensegrity Robot that can Navigate Among Obstacles

2025-11-08

AI Summary

Tensegrity robots—comprising rigid struts and elastic tendons—face significant challenges in inaccurate modeling, difficult control, and poor path planning and obstacle avoidance. Method: This paper introduces the first open-source, reproducible end-to-end autonomous navigation system for such robots. Our approach integrates physics-based modeling, system identification, robust state estimation, optimization-based path planning, and adaptive feedback control into a lightweight, integrated software stack. The hardware design is low-cost and open-source, enabling rapid deployment across multiple laboratories. Contribution/Results: We achieve the first robust autonomous navigation for underactuated tensegrity robots under unknown disturbances, successfully navigating collision-free in unstructured indoor and outdoor terrains—including vertical drops, steep slopes, and granular media. Crucially, coordinated experiments across two independent laboratories empirically validate the system’s reproducibility and cross-environment transferability.

Technology Category

• Intelligent Robots: Motion and Path Planning
• Multiagent Systems: Multiagent Systems under Uncertainty
• Planning, Routing, and Scheduling: Mixed Discrete/Continuous Planning

Application Category

• Responsible Web: Machine-in-the-loop, human agency and autonomy
• Systems and Infrastructure for Web, Mobile and WoT: Experiences and lessons learnt from Web-based algorithms and system deployments
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods

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.

Problem

• Develops a reproducible tensegrity robot system for obstacle navigation
• Addresses modeling and control challenges in compliant robot dynamics
• Enables collision-free path planning in unstructured terrain environments

Innovation

• Open-source hardware design for tensegrity robot
• Integrated software stack for modeling and control
• Reproducible navigation system for obstacle avoidance