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Cited by 271Robotic Locomotion and ControlNeurobiology and Insect Physiology ResearchBiomimetic flight and propulsion mechanisms

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Walknet—a biologically inspired network to control six-legged walking

Cruse, Holk, Kindermann, Thomas, Schumm, Michael, Dean, Jeffrey, Schmitz, Josef·1998·Neural Networks
DOI 10.1016/s0893-6080(98)00067-7
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Abstract

To investigate walking we perform experimental studies on animals in parallel with software and hardware simulations of the control structures and the body to be controlled. Therefore, the primary goal of our simulation studies is not so much to develop a technical device, but to develop a system which can be used as a scientific tool to study insect walking. To this end, the animat should copy essential properties of the animals. In this review, we will first describe the basic behavioral properties of hexapod walking, as the are known from stick insects. Then we describe a simple neural network called Walknet which exemplifies these properties and also shows some interesting emergent properties. The latter arise mainly from the use of the physical properties to simplify explicit calculations. The model is simple too, because it uses only static neuronal units. Finally, we present some new behavioral results.

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  • Two prominent mechanisms have been proposed for insect locomotion: a centralized mechanism that depends on coupled CPGs, and a more decentralized approach whereby locomotion emerges from the application of sensory feedback-based rules that dictate for each leg when to lift, swing, or remain in stance phase.

    “Two prominent mechanisms have been proposed for insect locomotion. The first is a centralized mechanism that depends on coupled CPGs (i.e., circuits producing rhythmic motor output without rhythmic input 58 ). The second is a more decentralized approach whereby locomotion emerges from the application of sensory feedback-based rules that dictate for each leg when to lift, swing, or remain in stance”

    From NeuroMechFly v2: simulating embodied sensorimotor control in adult Drosophila (2024) · cites this paper as [1]

  • The second rule ensures the propagation of the wave by eliciting a swing in the rostral and contralateral neighbor of a leg entering stance phase.

    “The second rule ensures the propagation of the wave by eliciting a swing in the rostral and contralateral neighbor of a leg entering stance phase.”

    From NeuroMechFly v2: simulating embodied sensorimotor control in adult Drosophila (2024) · cites this paper as [1]

  • The first rule ensures stability by inhibiting swing onset in the rostral neighbor of a swinging leg.

    “The first rule ensures stability by inhibiting swing onset in the rostral neighbor of a swinging leg.”

    From NeuroMechFly v2: simulating embodied sensorimotor control in adult Drosophila (2024) · cites this paper as [1]

  • The third rule enforces temporal coherence by eliciting a swing in the caudal and contralateral neighbor of a leg approaching the end of its stance phase.

    “The third rule enforces temporal coherence by eliciting a swing in the caudal and contralateral neighbor of a leg approaching the end of its stance phase.”

    From NeuroMechFly v2: simulating embodied sensorimotor control in adult Drosophila (2024) · cites this paper as [1]

Citations

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Metadata

Authors
Cruse, H., Kindermann, T., Schumm, M., Dean, J., & Schmitz, J.
Affiliations
  • Bielefeld University (DE)
  • Cleveland State University (US)
Corresponding author
Cruse, Holk
ORCID
Schmitz, Josef
Venue
Neural Networks
Publisher
Elsevier BV
Published
1998-10
Volume
11
Issue
7-8
Pages
1435-1447
ISSN
0893-6080 (ISSN-L)
DOI
10.1016/s0893-6080(98)00067-7
OpenAlex
W1999052969
Cited by
271
References
1
Citations by year
2026: 6 · 2025: 1 · 2024: 4 · 2023: 6 · 2022: 4 · 2021: 6 · 2020: 5 · 2019: 8 · 2018: 12 · 2017: 16 · 2016: 6 · 2015: 13 · 2014: 15 · 2013: 12 · 2012: 9
FWCI
7.31
Type
journal article
Language
en
Open access
closed
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Neural Networks (publishedVersion)
  • PubMed (publishedVersion)
  • EngagedScholarship @ Cleveland State University (Cleveland State University) (submittedVersion)
  • PUB – Publications at Bielefeld University (Bielefeld University) (submittedVersion)
Funders
  • Deutsche Forschungsgemeinschaft
  • Körber-Stiftung
Topics
  • Physical Sciences › Engineering › Control and Systems Engineering › Robotic Locomotion and Control
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurobiology and Insect Physiology Research
  • Physical Sciences › Engineering › Aerospace Engineering › Biomimetic flight and propulsion mechanisms
Keywords
insect locomotion, stick insects, bio-inspired control, neural network model, animats, emergent behavior, gait simulation

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