Authors:
Yuta Umemura
;
Ikuo Suzuki
;
Masahito Yamamoto
and
Masashi Furukawa
Affiliation:
Hokkaido University, Japan
Keyword(s):
Artificial life, Physics modelling, Jumping, RCGA, Behavior simple, Behavior composed.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Artificial Life
;
Computational Intelligence
;
Evolutionary Computing
;
Evolutionary Robotics and Intelligent Agents
;
Genetic Algorithms
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Soft Computing
Abstract:
Walking and jumping are very effective movement in a debris area. However, it is difficult to jump successively because it has a lot of difficulties (e.g. controlling the strong power at taking off and suppressing an impact at landing). This paper proposes how to acquire the successive jumping motion. We model an artificial creature like a locust under the physical virtual environment and control it by using Artificial Neural Network (ANN). In order to realize the successive jumping motion, this paper proposes a concept of “Behavior Simple (BS)” and “Behavior Composed (BC)”. The concept of BC is that a complex behavior is composed of plural simple behaviors. We consider that the successive jumping is divided into three BSs, taking off, getting up and returning leg back motion. After three BSs are trained by using the Real-Coded Genetic Algorithm (RCGA) independently, BC is trained by using RCGA as well. Experiments verify that the efficient successive jumping can be acquired.