Swarm Robots and Data Mining

My current work is about extracting some "Higher Knowledge" using Data Mining on the log data collect from external sensors like a camera. Before going any further, let me tell you about the kind of robots I am using here.

1. The price of one robot is around 20K JPY or US$ 200. 
2. It runs on a 6V battery. It has two motors to control its motion.
3. It uses only 3 IR sensors to detect obstacles.
4. There is no way, we can store on-board signals (for instance, IR readings) and analyse it off-line using a computer. 
5. It does not have any communication capabilities (like wireless, radio or blue tooth) with which it can communicate with other agents or with a central computer.

Hence the controller design completely depends on the designer who 'observes' the robot behaviour during its motion (say using his eyes, or a camera) and then based on his understanding, he modifies the controller to improve its performance  while achieving certain goals.

Now, our purpose is to build a system, where behaviour of several robots are analysed using data mining methods and useful hints are derived which could be used by the designer to improve the controller. The story is like this ...

A designer (a person) writes an algorithm for the swarm robots to perform a task and then goes away at night for sleep. During his absence, robot behaviour is recorded through an external sensory system (say multiple camera system in a building).  An autonomous data mining system (ADMS) analyses these logs and finds out if any robot manifested any kind of anomalous behaviour. It also enumerates the possible causes for such a behaviour and suggests some improvements that could be incorporated to overcome this anomaly. So in the morning, the designer comes back and analyses the results. He either incorporates the suggestion made by the ADMS in improving the controller or rejects its suggestions. 

This sounds more like science fiction at this stage. However, we have just started working on it ... Following video shows the motion of 4 robots which have been programmed to avoid obstacles (walls or other agents) while navigating the workspace. In this task, the robots are to be designed to increase the patrol rate which is the rate at which robot explores the workspace.