Title :
Obstacles Avoidance in a Self Path Plannning of a Polar Robot
Author :
J., Carlos ; Gorrostieta-Hurtado, E. ; Perez-Meneses, Joaquin
Author_Institution :
Mech. Eng. Dept., Technol. Inst. of Queretaro
Abstract :
The control of a robot´s movement in the self path planning problem requires the balance between time response and task requirements. In the case of robotic arms, both conditions are essential to turn a task efficient enough to be included into a productive environment. The robot´s movement has been researched several times trying to give them the capability of establishing a proper response under specific conditions without human interference. To achieve this goal, several strategies have been used, including spatial maps, area sweeping, iterative models and, as in this case, a neural genetic algorithm, in which the genetic algorithm builds the path based in a set of spatial positions, and the neural network learns from each of these paths to associate them with future positions and tasks. The target, is to adjust the robot´s performance to a level in which it is able to self define if a new path requires a searching process, if a previous sequence can be used, or if the points that conform the movement structure need to be adjusted in accordance to the accuracy needed
Keywords :
collision avoidance; genetic algorithms; industrial robots; mobile robots; neural nets; genetic algorithm; industrial robot; neural network; obstacles avoidance; polar robot; productive environment; robot movement control; self path planning; Genetic algorithms; Humans; Interference; Mechanical engineering; Orbital robotics; Path planning; Robot control; Robot sensing systems; Robotics and automation; Service robots;
Conference_Titel :
Electronics, Robotics and Automotive Mechanics Conference, 2006
Conference_Location :
Cuernavaca
Print_ISBN :
0-7695-2569-5
DOI :
10.1109/CERMA.2006.69