Name
Abstract | ||
|---|---|---|
Correlation based algorithms have been found to explain many basic behaviors in simple animals. In this paper we investigate the problem of navigation control of a robot from the viewpoint of bio-inspired perception. In this paper we study how to go up, through learning, from the implementation of a reactive system, towards behaviors of increasing complexity. The whole control system is based on networks of spiking neurons. A correlation based rule, namely the Spike Timing Dependent Plasticity (STDP), is implemented for an efficient learning. The main interesting consequence is that the system will be able to learn high-level sensor features, based on a set of basic reflexes, depending on some low-level sensor inputs. The whole methodology is presented through simulation results and also through its implementation on an FPGA based system for real time working on a roving robot. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ISCAS.2007.378811 | ISCAS |
Keywords | Field | DocType |
collision avoidance,field programmable gate arrays,learning (artificial intelligence),mobile robots,neural nets,sensors,visual perception,FPGA,bio-inspired perception,field programmable gate arrays,robot navigation,spike timing dependent plasticity,spiking neurons | Computer science,Field-programmable gate array,Artificial intelligence,Control system,Spike-timing-dependent plasticity,Robot,Artificial neural network,Reactive system,Level sensor,Mobile robot,Machine learning | Conference |
ISSN | Citations | PageRank |
0271-4302 | 7 | 0.59 |
References | Authors | |
6 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Paolo Arena | 1 | 261 | 47.43 |
| Luigi Fortuna | 2 | 761 | 128.37 |
| Mattia Frasca | 3 | 313 | 60.35 |
| Luca Patané | 4 | 104 | 17.31 |
| C. Sala | 5 | 7 | 0.59 |