Evolutionary Multi-Objective Optimization for Biped Walking

Authors:
Toshihiko Yanase;Hitoshi Iba
Affiliations:
Graduate School of Frontier Sciences, The University of Tokyo, Japan;Graduate School of Frontier Sciences, The University of Tokyo, Japan
Venue:
SEAL '08 Proceedings of the 7th International Conference on Simulated Evolution and Learning
Year:
2008

Citing 3
Cited 0

A real-coded genetic algorithm using the unimodal normal distribution crossover

Advances in evolutionary computing
Multi-agent learning of heterogeneous robots by evolutionary subsumption

GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
A fast and elitist multiobjective genetic algorithm: NSGA-II

IEEE Transactions on Evolutionary Computation

Quantified Score

Hi-index	0.00

Visualization

Abstract

We introduce an application of Evolutionary Multi- Objective Optimization on multi-layered robot control system. Recent robot control systems consist of many simple function modules. The parameter settings for most of these modules were manually adjusted in previous research. Our goal is to develop an automatic parameter adjustment method for the robot control system. In this paper, we focused on three modules as the experiment environment: whole-body motion generator, footstep planner and path planner. At first the features of these three modules are examined. Then we discuss the trade-off relationship between the requirements of each module. Finally, we examined an application of Evolutionary Multi-Objective Optimization on this problem.