Evolutionary behavior acquisition for humanoid robots

Authors:
Deniz Aydemir;Hitoshi Iba
Affiliations:
Graduate School of Frontier Sciences, Department of Frontier Informatics, Tokyo University, Tokyo, Japan;Graduate School of Frontier Sciences, Department of Frontier Informatics, Tokyo University, Tokyo, Japan
Venue:
PPSN'06 Proceedings of the 9th international conference on Parallel Problem Solving from Nature
Year:
2006

Citing 3
Cited 0

Issues in evolutionary robotics

Proceedings of the second international conference on From animals to animats 2 : simulation of adaptive behavior: simulation of adaptive behavior
RapidAccurate Optimization of Difficult Problems Using Fast Messy Genetic Algorithms

Proceedings of the 5th International Conference on Genetic Algorithms
Evolutionary motion design for humanoid robots

Proceedings of the 8th annual conference on Genetic and evolutionary computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper describes and analyzes a series of experiments to develop a general evolutionary behavior acquisition technique for humanoid robots. The robot's behavior is defined by joint controllers evolved concurrently. Each joint controller consists of a series of primitive actions defined by a chromosome. By using genetic algorithms with specifically designed genetic operators and novel representations, complex behaviors are evolved from the primitive actions defined. Representations are specifically tailored to be useful in trajectory generation for humanoid robots. The effectiveness of the method is demonstrated by two experiments: a handstand and a limbo dance behavioral tasks (leaning the body backwards so as to pass under a fixed height bar).