ArticleFrontiers in neurorobotics2010
A 3D Musculo-Mechanical Model of the Salamander for the Study of Different Gaits and Modes of Locomotion.
Article in Frontiers in neurorobotics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Balancing central control and sensory feedback produces adaptable and robust locomotor patterns in a spiking, neuromechanical model of the salamander spinal cord.PLoS computational biology · 2025Article
- Spontaneous Gait Transitions of Sprawling Quadruped Locomotion by Sensory-Driven Body-Limb Coordination Mechanisms.Frontiers in neurorobotics · 2021Article
- Control for multifunctionality: bioinspired control based on feeding in Aplysia californica.Biological cybernetics · 2020Article
- Reproducing Five Motor Behaviors in a Salamander Robot With Virtual Muscles and a Distributed CPG Controller Regulated by Drive Signals and Proprioceptive Feedback.Frontiers in neurorobotics · 2020Article
- Sensory feedback plays a significant role in generating walking gait and in gait transition in salamanders: a simulation study.Frontiers in neurorobotics · 2011Article
- Muscle co-contraction modulates damping and joint stability in a three-link biomechanical limb.Frontiers in neurorobotics · 2011Article
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Authors and funding
3 authors.
Funding
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Abstract
Computer simulation has been used to investigate several aspects of locomotion in salamanders. Here we introduce a three-dimensional forward dynamics mechanical model of a salamander, with physically realistic weight and size parameters. Movements of the four limbs and of the trunk and tail are generated by sets of linearly modeled skeletal muscles. In this study, activation of these muscles were driven by prescribed neural output patterns. The model was successfully used to mimic locomotion on level ground and in water. We compare the walking gait where a wave of activity in the axial muscles travels between the girdles, with the trotting gait in simulations using the musculo-mechanical model. In a separate experiment, the model is used to compare different strategies for turning while stepping; either by bending the trunk or by using side-stepping in the front legs. We found that for turning, the use of side-stepping alone or in combination with trunk bending, was more effective than the use of trunk bending alone. We conclude that the musculo-mechanical model described here together with a proper neural controller is useful for neuro-physiological experiments in silico.
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