Flexible Spiking CPGs for Online Manipulation During Hexapod Walking.

ABSTRACT: Neural signals for locomotion are influenced both by the neural network architecture and sensory inputs coordinating and adapting the gait to the environment. Adaptation relies on the ability to change amplitude, frequency, and phase of the signals within the sensorimotor loop in response to external stimuli. However, in order to experiment with closed-loop control, we first need a better understanding of the dynamics of the system and how adaptation works. Based on insights from biology, we developed a spiking neural network capable of continuously changing amplitude, frequency, and phase online. The resulting network is deployed on a hexapod robot in order to observe the walking behavior. The morphology and parameters of the network results in a tripod gait, demonstrating that a design w

SUBMITTER: Strohmer B 

PROVIDER: S-EPMC7333644 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature