A simple robust robotic vision system using Kohonen feature mapping

We use a one-dimensional Kohonen network for detecting the angular position of an infrared beacon in front of an experimental autonomous vehicle. The inputs to the Kohonen network are the analog output signals from eight infrared detectors arranged along a semi-circle on the front of the vehicle. By letting the network self-organise while a beacon is moved from one side to the other in front of the sensors a linear mapping of angles on neurons emerges. The mapping is robust against alignment errors, differences in sensitivity and even total failure of some sensors. A two-dimensional Kohonen network can even detect distances with the same sensor array