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Showing 1–3 of 3 results
Advanced filters: Author: Auke Jan Ijspeert Clear advanced filters

  • Traditional feedback-state selection in robot learning is empirical and requires substantial engineering efforts. Yu et al. develop a quantitative and systematic state-importance analysis, revealing crucial feedback signals for learning locomotion skills.

    • Wanming Yu
    • Chuanyu Yang
    • Zhibin Li
    ResearchOpen Access
    Nature Machine Intelligence
    Volume: 5, P: 919-932

  • NeuroMechFly enables simulations of adult Drosophila melanogaster. The platform combines a biomechanical representation of the fly body, models of the muscles, a neural controller and a physics-based simulation of the environment.

    • Victor Lobato-Rios
    • Shravan Tata Ramalingasetty
    • Pavan Ramdya
    Research
    Nature Methods
    Volume: 19, P: 620-627

  • Numerous selective forces shape animal locomotion patterns and as a result, different animals evolved to use different gaits. Here, Ramdyaet al. use live and in silicoDrosophila, as well as an insect-model robot, to gain insights into the conditions that promote the ubiquitous tripod gait observed in most insects.

    • Pavan Ramdya
    • Robin Thandiackal
    • Dario Floreano
    ResearchOpen Access
    Nature Communications
    Volume: 8, P: 1-11