Evidence map›Paper›PMID 28878645›Full record

ReviewFrontiers in neurorobotics2017

Adaptive Control Strategies for Interlimb Coordination in Legged Robots: A Review.

Shinya Aoi, Poramate Manoonpong, Yuichi Ambe, Fumitoshi Matsuno, Florentin Wörgötter

Abstract readReview
In one paragraph

Review in Frontiers in neurorobotics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 37 papers.

0numbers the graph read from it
0cells of the map it votes in
37citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

37 citing papers in PubMed.

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  20. Fast and Slow Adaptations of Interlimb CoordinationFrontiers in robotics and AI · 2021
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Shinya AoiDepartment of Aeronautics and Astronautics, Graduate School of Engineering, Kyoto UniversityKyoto, Japan.
Poramate ManoonpongEmbodied AI & Neurorobotics Lab, Centre for Biorobotics, Mærsk Mc-Kinney Møller Institute, University of Southern DenmarkOdense, Denmark.
Yuichi AmbeDepartment of Applied Information Sciences, Graduate School of Information Sciences, Tohoku UniversityAoba-ku, Japan.
Fumitoshi MatsunoDepartment of Mechanical Engineering and Science, Graduate School of Engineering, Kyoto UniversityKyoto, Japan.
Florentin WörgötterBernstein Center for Computational Neuroscience, Third Institute of Physics, Georg-August-Universität GöttingenGöttingen, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Walking animals produce adaptive interlimb coordination during locomotion in accordance with their situation. Interlimb coordination is generated through the dynamic interactions of the neural system, the musculoskeletal system, and the environment, although the underlying mechanisms remain unclear. Recently, investigations of the adaptation mechanisms of living beings have attracted attention, and bio-inspired control systems based on neurophysiological findings regarding sensorimotor interactions are being developed for legged robots. In this review, we introduce adaptive interlimb coordination for legged robots induced by various factors (locomotion speed, environmental situation, body properties, and task). In addition, we show characteristic properties of adaptive interlimb coordination, such as gait hysteresis and different time-scale adaptations. We also discuss the underlying mechanisms and control strategies to achieve adaptive interlimb coordination and the design principle for the control system of legged robots.

Indexed as

adaptationcentral pattern generatorinterlimb coordinationlegged robotsensorimotor interaction

Identifiers

PMID28878645
PMCPMC5572352

What OpenQuestion holds

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Registered trials

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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.