In the narrative on YouTube Nicolas writes
This video shows a fully autonomous artificial evolution within a population of ~20 completely autonomous real (e-puck) robots. Each robot is driven by its "genome" and genomes are spread whenever robots are close enough (range: 25cm). The most "efficient" genomes end up being those that successfully drive robots to meet with each other while avoiding getting stuck in a corner.
There is no human-defined pressure on robot behavior. There is no human-defined objective to perform.
The environment alone puts pressure upon which genomes will survive (ie. the better the spread, the higher the survival rate). Then again, the ability for a genome to encode an efficient behavioral strategy first results from pure chance, then from environmental pressure.
In this video, you can observe how going towards the sun naturally emerges as a good strategy to meet/mate with other (it is used as a convenient "compass") and how changing the sun location affect robots behavior.
Note: the 'sun' is the static e-puck with a white band around it.