Implementing neural soft- and hardware on the autonomous mini-robot Khepera

The applicability of neural networks to generate complex behaviour on autonomous systems is demonstrated both at soft- and hardware-level. In particular, the emergence of simple behaviors based on the Braitenberg approach, adaptive sensor calibration by self-organizing maps with a comparison between off- and online learning and a visualisation tool for a posteriori analysis are shown. It is also envisaged to present the working of embedded neural hardware as associative memory and self-organizing maps. In this connection, the mini-robot Khepera serves as an exemplary platform