Evolving hierarchical robot behaviours

Inspired by the work of Brooks, many researchers involved in programming robots have turned to the behaviour-based approach. At present, the behaviours are designed by hand and hard-wired into the architecture. The work presented in this paper looks at using an evolutionary algorithm approach (based on the genetic algorithm) to construct behaviours. Building from well-defined primitive behaviours, hierarchies can be evolved to produce more complex behaviour. The behaviours in the evolutionary system are tested in simulation, but the best are then tested on a mobile robot for grounding in the real world. This allows the evolutionary process to rapidly drive the development of the behaviours using simulation while also ensuring their suitability in the real world. In the paper we show how this evolutionary process evolves practical hierarchical behaviours for the detection of a goal object in a series of mazes.