Multi-objective evolution of robot neuro-controllers

Amiram Moshaiov*, Ariela Ashram

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


This paper concerns a non-traditional evolutionary robotics approach to robot navigation. Navigation is presented as a problem of two conflicting objectives. The first concerns a classical "amalgamated" objective, which has been traditionally used to increase speed, move straight as possible, and at the same time avoid obstacles. The second objective is devised to simultaneously encourage a sequential acquisition of targets. To solve the presented problem a modification of the well known NSGAII algorithm has been performed. The proposed approach is tested using a simulation of a Khepera. The study sheds light on different aspects of the aforementioned problem and on the applicability of evolutionary multi-objective optimization to the simultaneous learning of a variety of controllers for deferent behaviors. Finally, based on this initial study, future work is suggested, which may allow to shift such multiobjective evolutionary studies from toy problems to more realistic situations.

Original languageEnglish
Title of host publication2009 IEEE Congress on Evolutionary Computation, CEC 2009
Number of pages8
StatePublished - 2009
Event2009 IEEE Congress on Evolutionary Computation, CEC 2009 - Trondheim, Norway
Duration: 18 May 200921 May 2009

Publication series

Name2009 IEEE Congress on Evolutionary Computation, CEC 2009


Conference2009 IEEE Congress on Evolutionary Computation, CEC 2009


Dive into the research topics of 'Multi-objective evolution of robot neuro-controllers'. Together they form a unique fingerprint.

Cite this