Title :
Cooperative genetic algorithms: a new approach to solve the path planning problem for cooperative robotic manipulators sharing the same work space
Author :
De la Cueva, Victor ; Ramos, Fernando
Author_Institution :
Div. de Ingenieria y Cuiencias, ITESM, Cuernavaca, Mexico
Abstract :
A new approach for planning paths without collisions for two robots sharing the same work space based on a new kind of genetic algorithm that we have called cooperative genetic algorithms (CGA) is presented. Each robot is associated with a population of the CGA. The cooperation is carried out through an interaction between populations until they find collision-free paths for both robots. The fitness function of the CGA considers reaching the goal without collisions by using a minimal number of robotic configurations. The main advantages of this approach are: it is not necessary either to use the composite C-Space or a kinematic model based on a Jacobian matrix; this method can be used for both redundant and nonredundant robots
Keywords :
cooperative systems; genetic algorithms; intelligent control; manipulators; multi-robot systems; optimal control; path planning; CGA; collision-free paths; cooperative genetic algorithms; cooperative robotic manipulators; fitness function; nonredundant robots; path planning problem; redundant robots; robotic configurations; Chromium; Genetic algorithms; Jacobian matrices; Kinematics; Manipulators; Orbital robotics; Path planning; Road accidents; Robot control; Time sharing computer systems;
Conference_Titel :
Intelligent Robots and Systems, 1998. Proceedings., 1998 IEEE/RSJ International Conference on
Conference_Location :
Victoria, BC
Print_ISBN :
0-7803-4465-0
DOI :
10.1109/IROS.1998.724630