The Proceedings of JSME annual Conference on Robotics and Mechatronics (Robomec)
Online ISSN : 2424-3124
2012
Session ID : 1A2-E08
Conference information
1A2-E08 Acquisition of Jumping Behavior on the Locust Model under Virtual Physical Environment(Evolution and Learning for Robotics(2))
Yuta UMEMURAIkuo SUZUKIMasahito YAMAMOTOMasashi FURUKAWA
Author information
CONFERENCE PROCEEDINGS FREE ACCESS

Details
Abstract
This paper proposes how to acquire the composite behavior composed of the jumping, landing and walking behavior on artificial creature like a locust under the physical virtual environment. We acquires such behaviors by use of neuroevolution. Neuroevolution is one of the learning algorithm composed of artificial neural network(ANN) and real-coded genetic algorithm (RCGA) and we acquire optimized behavior of the locust model by use of it. In this study, we realize the jumping behavior first. After that, we realize the landing behavior to fix the posture of the locust model. Finally, we realize the walking behavior. We analyze the obtained behavior.
Content from these authors
© 2012 The Japan Society of Mechanical Engineers
Previous article Next article
feedback
Top