Name
Abstract | ||
|---|---|---|
This article describes an FPGA (Field Programmable Gate Array) based hardware implementation of a genetic controller to be applied for the evolution of an Artificial Neural Network (ANN) [3] for collision-free navigation task of mobile robots. The adaptive nature of ANN enables it to train itself while the robot interacts with the environment. In addition to online training, the genetic evolution in neuron bits will be examined in an experiment to understand the interaction between evolution and lifetime adaptation of the ANN. The concept of chromosome for navigation task, design techniques of various blocks inside the GA controller will be elaborately described here. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/3-540-36553-2_31 | ICES |
Keywords | Field | DocType |
genetic controller,design technique,genetic evolution,hardware implementation,adaptive nature,artificial neural network,collision-free navigation task,navigation task,ga controller,field programmable gate array,genetics,mobile robot | Control theory,Genetic Evolution,Computer science,Field-programmable gate array,Artificial intelligence,Artificial neural network,Robot,Computer hardware,Genetic algorithm,Mobile robot,Robotics | Conference |
Volume | ISSN | ISBN |
2606 | 0302-9743 | 3-540-00730-X |
Citations | PageRank | References |
1 | 0.41 | 4 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. A. Hannan Bin Azhar | 1 | 11 | 4.15 |
| K. R. Dimond | 2 | 11 | 3.86 |