an evolutionary approach to gait learning for four-legged robots
Author(s): Sonia Chernova, Manuela Veloso
Venue: International Conference on Intelligent Robots and Systems
Year Published: 2004
Keywords: planning, mobile robots, evolution, legged robots, genetic algorithms, locomotion
Expert Opinion: This paper presents a clear and concrete mapping of genetic algorithms to a compelling hardware domain: Sony AIBO walking gait and the RoboCup soccer competition. The AIBO was an example of a platform where parameter tuning by hand is particularly tedious (54 parameters), plus the platform was safe to have "practice‚" on its own overnight (i.e. without human supervision, a rarity for mobile robots)---offering an opportunity for fully autonomous and on-hardware optimization-based learning, where it was feasible for each generation to be evaluated (according to the fitness function) on the actual robot platform without human supervision or intervention. The learned walk that resulted outperformed all hand-tuned and learned walks that participated in (including that which won) the RoboCup 2003 competition. ** This recommendation is getting a bit into the weeds of specific algorithms---not quite sure if the list is planning to go that deep. It's a work I would present in a class, as a great example of a CS algorithm being translated for use on real robot hardware. Again, not quite sure if that sort of categorization fits the bill.