ArticleiScience2021
Achieving natural behavior in a robot using neurally inspired hierarchical perceptual control.
Article in iScience, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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
3 citing papers in PubMed.
- Aligning brain and behavior.Current opinion in behavioral sciences · 2025Article
- Intrinsic Motivation as Constrained Entropy Maximization.Entropy (Basel, Switzerland) · 2025Article
- Interoception as modeling, allostasis as control.Biological psychology · 2022Article
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Authors and funding
2 authors.
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Abstract
Terrestrial locomotion presents tremendous computational challenges on account of the enormous degrees of freedom in legged animals, and complex, unpredictable properties of natural environments, including the body and its effectors, yet the nervous system can achieve locomotion with ease. Here we introduce a quadrupedal robot that is capable of posture control and goal-directed locomotion across uneven terrain. The control architecture is a hierarchical network of simple negative feedback control systems inspired by the organization of the vertebrate nervous system. This robot is capable of robust posture control and locomotion in novel environments with unpredictable disturbances. Unlike current robots, our robot does not use internal inverse and forward models, nor does it require any training in order to perform successfully in novel environments.
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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.