ArticleSoft robotics2018
Adaptive and Resilient Soft Tensegrity Robots.
Article in Soft robotics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- What is Balance? A Vital Mechano-Regulation Paradigm.Open mind : discoveries in cognitive science · 2025Article
- Spikebot: A Multigait Tensegrity Robot with Linearly Extending Struts.Soft robotics · 2024Article
- Morphing-Enabled Path Planning for Flying Tensegrity Robots as a Semidefinite Program.Frontiers in robotics and AI · 2022Article
- Task space adaptation via the learning of gait controllers of magnetic soft millirobots.The International journal of robotics research · 2021Article
- Reafference and the origin of the self in early nervous system evolution.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2021Review
- Editorial: Recent Trends in Morphological Computation.Frontiers in robotics and AI · 2021Article
- Phase Changing Materials-Based Variable-Stiffness Tensegrity Structures.Soft robotics · 2020Article
- Rolling Locomotion of Cable-Driven Soft Spherical Tensegrity Robots.Soft robotics · 2020Article
- Learning of Sub-optimal Gait Controllers for Magnetic Walking Soft Millirobots.Robotics science and systems : online proceedings · 2020Article
Corrections and comments
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Authors and funding
2 authors.
Funding
Abstract
Living organisms intertwine soft (e.g., muscle) and hard (e.g., bones) materials, giving them an intrinsic flexibility and resiliency often lacking in conventional rigid robots. The emerging field of soft robotics seeks to harness these same properties to create resilient machines. The nature of soft materials, however, presents considerable challenges to aspects of design, construction, and control-and up until now, the vast majority of gaits for soft robots have been hand-designed through empirical trial-and-error. This article describes an easy-to-assemble tensegrity-based soft robot capable of highly dynamic locomotive gaits and demonstrating structural and behavioral resilience in the face of physical damage. Enabling this is the use of a machine learning algorithm able to discover effective gaits with a minimal number of physical trials. These results lend further credence to soft-robotic approaches that seek to harness the interaction of complex material dynamics to generate a wealth of dynamical behaviors.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.