Name
Abstract | ||
|---|---|---|
The employment of Field Programmable Gate Arrays (FPGAs) to a robot controller is very attractive, since it allows fast IC prototyping and low cost modifications. The speedup is achieved because of pipelining and dedicated functions in hardware that are customized to the problems. The self learning ability and the adaptive nature of an Artificial Neural Network (ANN) makes it a good candidate for the control structure of a robot's navigation. Evolutionary approach in designing robots can evolve the architecture of ANNs and yields automatic creation of the controller while the robot moves in task environments. This article briefly describes the important hardware issues involved with the FPGA based design of an evolutionary robot controller for the collision free navigation of mobile robots. |
Year | Venue | Keywords |
|---|---|---|
2003 | MLMTA'03: INTERNATIONAL CONFERENCE ON MACHINE LEARNING; MODELS, TECHNOLOGIES AND APPLICATIONS | FPGA,ANN,GA,evolutionary robotics |
Field | DocType | Citations |
Robot control,Control theory,Computer science,Field-programmable gate array,Mobile robot,Embedded system,Mobile manipulator | Conference | 0 |
PageRank | References | Authors |
0.34 | 1 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| M. A. Hannan Bin Azhar | 1 | 11 | 4.15 |
| Keith R. Dimond | 2 | 9 | 2.12 |