Distributed recurrent neural forward models with synaptic adaptation and CPG-based control for complex behaviors of walking robots.

ABSTRACT: Walking animals, like stick insects, cockroaches or ants, demonstrate a fascinating range of locomotive abilities and complex behaviors. The locomotive behaviors can consist of a variety of walking patterns along with adaptation that allow the animals to deal with changes in environmental conditions, like uneven terrains, gaps, obstacles etc. Biological study has revealed that such complex behaviors are a result of a combination of biomechanics and neural mechanism thus representing the true nature of embodied interactions. While the biomechanics helps maintain flexibility and sustain a variety of movements, the neural mechanisms generate movements while making appropriate predictions crucial for achieving adaptation. Such predictions or planning ahead can be achieved by way of internal mo

SUBMITTER: Dasgupta S 

PROVIDER: S-EPMC4585172 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature