Paper Info
Title
A comparative study between genetic algorithm and genetic programming based gait generation methods for quadruped robots
Abstract
Planning gaits for legged robots is a challenging task that requires optimizing parameters in a highly irregular and multidimensional space. Two gait generation methods using GA (Genetic Algorithm), GP (genetic programming) are compared to develop fast locomotion for a quadruped robot. GA-based approaches seek to optimize a pre-selected set of parameters which include locus of paw and stance parameters of initial position. A GP-based technique is an effective way to generate a few joint trajectories instead of the locus of paw positions and many stance parameters. Optimizations for two proposed methods are executed and analyzed using a Webots simulation of the quadruped robot built by Bioloid. Furthermore, simulation results for the two proposed methods are tested in a real quadruped robot, and the performance and motion features of GA-, GP -based methods are compared.
Year
DOI
Venue
2010
10.1007/978-3-642-12239-2_37
EvoApplications (1)
Keywords
Field
DocType
real quadruped robot,genetic algorithm,gait generation method,simulation result,webots simulation,quadruped robot,paw position,comparative study,gp-based technique,genetic programming,legged robot,ga-based approach,stance parameter
Gait,Computer science,Genetic programming,Artificial intelligence,Robot,Genetic algorithm
Conference
Volume
ISSN
ISBN
6024
0302-9743
3-642-12238-8
Citations 
PageRank 
References 
2
0.42
7
Authors
2
Name
Order
Citations
PageRank
Kisung Seo114118.95
Soohwan Hyun2244.18