Abstract
An artificial bionic neural network to control fish-robot locomotion is presented. The fish-robot, which is inspired from “ Gymnarchus niloticus”, is modeled as a multi-joint dynamic system with parallel connections and composed of several motors. The principle of the central pattern generators (CPGs) governing the locomotion of fish is analyzed. An artificial neural network which has many comparability with the biological CPGs is designed to control the fish-robot. Experimental results of startup, stop, forward swimming and backward swimming show its validity and efficiency.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
