Introduction to artificial neural systems
Introduction to artificial neural systems
Introduction to Robotics: Mechanics and Control
Introduction to Robotics: Mechanics and Control
Analysis of Mechanisms and Robot Manipulators
Analysis of Mechanisms and Robot Manipulators
Neural Networks: A Comprehensive Foundation
Neural Networks: A Comprehensive Foundation
Inverse velocity analysis for line guidance five-axis robots
Robotics and Computer-Integrated Manufacturing
Advances in Engineering Software
Optimum robot manipulator path generation using differential evolution
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Engineering Applications of Artificial Intelligence
International Journal of Automation and Computing
Contour Tracking of a Redundant Robot Using Integral Variable Structure Control with Output Feedback
Journal of Intelligent and Robotic Systems
Obstacle avoidance of redundant manipulators using neural networks based reinforcement learning
Robotics and Computer-Integrated Manufacturing
Information Sciences: an International Journal
Advances in Artificial Intelligence
Hi-index | 0.00 |
An adoptive learning strategy using an artificial neural network ANN has been proposed here to control the motion of a 6 D.O.F manipulator robot and to overcome the inverse kinematics problem, which are mainly singularities and uncertainties in arm configurations. In this approach a network have been trained to learn a desired set of joint angles positions from a given set of end effector positions, experimental results has shown an excellent mapping over the working area of the robot, to validate the ability of the designed network to make prediction and well generalization for any set of data, a new training using different data set has been performed using the same network, experimental results has shown a good generalization for the new data sets.The proposed control technique does not require any prior knowledge of the kinematics model of the system being controlled, the basic idea of this concept is the use of the ANN to learn the characteristics of the robot system rather than to specify explicit robot system model. Any modification in the physical set-up of the robot such as the addition of a new tool would only require training for a new path without the need for any major system software modification, which is a significant advantage of using neural network technology.