Evolving Motion Controllers for Articulated Robots

Articulated robots have a much more complex relationship between motor outputs and locomotion than wheel robots have. We can simplify this relationship using an abstraction layer of cyclic motor outputs corresponding to different kinds of locomotion. One way to create these cyclic motor outputs is by evolving a controller network consisting of oscillators, motor output nodes, and weighted edges. We evolved cyclic movements using this method, and found that simulated annealing and integral frequencies led to the fastest fitness growth. The final controllers resulted in fast and efficient movement. By changing the fitness function and adding sensor inputs, this technique could be extended to evolve movements that are robust and safe as well as