Title :
A neural network system that controls and plans paths for a robot
Author :
Garcia-Chamizo, J. ; Ibarra-Picó, F.
Author_Institution :
Dept. de Tecnologia Inf. y Comput., Alicante Univ., Spain
Abstract :
Proposes to solve the problems of direct/inverse kinematics and control of trajectories by multilevel perceptrons. The authors´ solution admits a parallel implementation in real time. It does not need either to solve kinematic equations or robot trajectories, because it learns gradually by examples adaptively. The control system consists of different networks each of which specialises in solving a particular problem. This structure enables a modular approach to the problem accelerating convergence. The system obtains an acceptable trajectory and gives a parallel solution that could be used in real-time applications
Keywords :
convergence; multilayer perceptrons; path planning; robot dynamics; robot kinematics; convergence; direct/inverse kinematics; multilevel perceptrons; neural network system; parallel implementation; robot; trajectories control; Acceleration; Adaptive systems; Backpropagation algorithms; Control systems; Equations; Kinematics; Neural networks; Orbital robotics; Real time systems; Robots;
Conference_Titel :
Industrial Automation and Control, 1995 (I A & C'95), IEEE/IAS International Conference on (Cat. No.95TH8005)
Conference_Location :
Hyderabad
Print_ISBN :
0-7803-2081-6
DOI :
10.1109/IACC.1995.465839
