ArticleFrontiers in neural circuits2020
General Distributed Neural Control and Sensory Adaptation for Self-Organized Locomotion and Fast Adaptation to Damage of Walking Robots.
Article in Frontiers in neural circuits, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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7 citing papers in PubMed.
- Artificial plateau neurons with in-situ spike-malleability for rhythmic quadrupedal locomotion.Nature communications · 2026Article
- Maneuverable and Efficient Locomotion of a Myriapod Robot with Variable Body-Axis Flexibility via Instability and Bifurcation.Soft robotics · 2023Article
- Robust and reusable self-organized locomotion of legged robots under adaptive physical and neural communications.Frontiers in neural circuits · 2023Article
- Leg-body coordination strategies for obstacle avoidance and narrow space navigation of multi-segmented, legged robots.Frontiers in neurorobotics · 2023Article
- Bio-inspired neural networks for decision-making mechanisms and neuromodulation for motor control in a differential robot.Frontiers in neurorobotics · 2023Article
- Insect-Inspired Robots: Bridging Biological and Artificial Systems.Sensors (Basel, Switzerland) · 2021Review
- A Comparative Study of Adaptive Interlimb Coordination Mechanisms for Self-Organized Robot Locomotion.Frontiers in robotics and AI · 2021Article
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2 authors.
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Abstract
Walking animals such as invertebrates can effectively perform self-organized and robust locomotion. They can also quickly adapt their gait to deal with injury or damage. Such a complex achievement is mainly performed via coordination between the legs, commonly known as interlimb coordination. Several components underlying the interlimb coordination process (like distributed neural control circuits, local sensory feedback, and body-environment interactions during movement) have been recently identified and applied to the control systems of walking robots. However, while the sensory pathways of biological systems are plastic and can be continuously readjusted (referred to as sensory adaptation), those implemented on robots are typically static. They first need to be manually adjusted or optimized offline to obtain stable locomotion. In this study, we introduce a fast learning mechanism for online sensory adaptation. It can continuously adjust the strength of sensory pathways, thereby introducing flexible plasticity into the connections between sensory feedback and neural control circuits. We combine the sensory adaptation mechanism with distributed neural control circuits to acquire the adaptive and robust interlimb coordination of walking robots. This novel approach is also general and flexible. It can automatically adapt to different walking robots and allow them to perform stable self-organized locomotion as well as quickly deal with damage within a few walking steps. The adaptation of plasticity after damage or injury is considered here as lesion-induced plasticity. We validated our adaptive interlimb coordination approach with continuous online sensory adaptation on simulated 4-, 6-, 8-, and 20-legged robots. This study not only proposes an adaptive neural control system for artificial walking systems but also offers a possibility of invertebrate nervous systems with flexible plasticity for locomotion and adaptation to injury.
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