5 papers
Model Predictive Control of Tensegrity Robots via Contact-Aware Graph Neural Dynamics Model
Nelson Chen, Patrick Meng, Charles Tang +5
Tensegrity robots offer lightweight, compliant mobility over challenging terrain but remain difficult to model and control due to complex contact-rich dynamics and partial observab…
CableRobotGraphSim: A Graph Neural Network for Modeling Partially Observable Cable-Driven Robot Dynamics
Nelson Chen, William R. Johnson, Rebecca Kramer-Bottiglio +2
General-purpose simulators have accelerated the development of robots. Traditional simulators based on first-principles, however, typically require full-state observability or depe…
An Open-Source, Reproducible Tensegrity Robot that can Navigate Among Obstacles
William R. Johnson, Patrick Meng, Nelson Chen +5
Tensegrity robots, composed of rigid struts and elastic tendons, provide impact resistance, low mass, and adaptability to unstructured terrain. Their compliance and complex, couple…
Impact-resistant, autonomous robots inspired by tensegrity architecture
William R. Johnson, Xiaonan Huang, Shiyang Lu +4
Future robots will navigate perilous, remote environments with resilience and autonomy. Researchers have proposed building robots with compliant bodies to enhance robustness, but t…
6N-DoF Pose Tracking for Tensegrity Robots
Shiyang Lu, William R. Johnson, Kun Wang +4
Tensegrity robots, which are composed of compressive elements (rods) and flexible tensile elements (e.g., cables), have a variety of advantages, including flexibility, low weight,…