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Impact-resistant, autonomous robots inspired by tensegrity architecture

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arxiv 2501.15078 v1 pith:6N5WAY6Q submitted 2025-01-25 cs.RO

classification cs.RO
keywords robotrobotstensegrityautonomousautonomyarchitecturecapabilitiesinspired
verification ladder T0 review T1 audit T2 compute T3 formal
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Future robots will navigate perilous, remote environments with resilience and autonomy. Researchers have proposed building robots with compliant bodies to enhance robustness, but this approach often sacrifices the autonomous capabilities expected of rigid robots. Inspired by tensegrity architecture, we introduce a tensegrity robot -- a hybrid robot made from rigid struts and elastic tendons -- that demonstrates the advantages of compliance and the autonomy necessary for task performance. This robot boasts impact resistance and autonomy in a field environment and additional advances in the state of the art, including surviving harsh impacts from drops (at least 5.7 m), accurately reconstructing its shape and orientation using on-board sensors, achieving high locomotion speeds (18 bar lengths per minute), and climbing the steepest incline of any tensegrity robot (28 degrees). We characterize the robot's locomotion on unstructured terrain, showcase its autonomous capabilities in navigation tasks, and demonstrate its robustness by rolling it off a cliff.

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Cited by 1 Pith paper

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score.

  1. CableRobotGraphSim: A Graph Neural Network for Modeling Partially Observable Cable-Driven Robot Dynamics

    cs.RO 2026-02 conditional novelty 5.0 of 10

    A fully learnable GNN predicts cable-driven tensegrity dynamics from partial observations and serves as the transition model for closed-loop MPPI navigation, beating differentiable physics baselines.

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