ArticleJournal of the Royal Society, Interface2010
Morphological communication: exploiting coupled dynamics in a complex mechanical structure to achieve locomotion.
Article in Journal of the Royal Society, Interface, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 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.
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Who cites it
10 citing papers in PubMed.
- Toward aitiopoietic cognition: bridging the evolutionary divide between biological and machine-learned causal systems.Frontiers in cognition · 2025Review
- Modularity of the Human Musculoskeletal System: The Correlation between Functional Structures by Computer Tools Analysis.Life (Basel, Switzerland) · 2022Article
- Synthetic living machines: A new window on life.iScience · 2021Review
- Editorial: Recent Trends in Morphological Computation.Frontiers in robotics and AI · 2021Article
- Morphological Computation Increases From Lower- to Higher-Level of Biological Motor Control Hierarchy.Frontiers in robotics and AI · 2020Article
- Locating the Inexhaustible: Material, Medium, and Ambient Information.Frontiers in psychology · 2020Review
- On neuromechanical approaches for the study of biological and robotic grasp and manipulation.Journal of neuroengineering and rehabilitation · 2017Review
- Exploring the high-dimensional structure of muscle redundancy via subject-specific and generic musculoskeletal models.Journal of biomechanics · 2015Article
- Design and control of compliant tensegrity robots through simulation and hardware validation.Journal of the Royal Society, Interface · 2014Article
- Computational Models for Neuromuscular Function.IEEE reviews in biomedical engineering · 2009Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
Traditional engineering approaches strive to avoid, or actively suppress, nonlinear dynamic coupling among components. Biological systems, in contrast, are often rife with these dynamics. Could there be, in some cases, a benefit to high degrees of dynamical coupling? Here we present a distributed robotic control scheme inspired by the biological phenomenon of tensegrity-based mechanotransduction. This emergence of morphology-as-information-conduit or 'morphological communication', enabled by time-sensitive spiking neural networks, presents a new paradigm for the decentralized control of large, coupled, modular systems. These results significantly bolster, both in magnitude and in form, the idea of morphological computation in robotic control. Furthermore, they lend further credence to ideas of embodied anatomical computation in biological systems, on scales ranging from cellular structures up to the tendinous networks of the human hand.
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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.