Transference of Evolved Unmanned Aerial Vehicle Controllers to a Wheeled Mobile Robot
Gregory J. Barlow, Leonardo S. Mattos, Edward Grant, and Choong K. Oh

Transference of controllers evolved in simulation to real vehicles is an 
important issue in evolutionary robotics (ER). We have previously evolved 
autonomous navigation controllers for fixed wing UAV applications using 
multi-objective genetic programming (GP). Controllers were evolved to 
locate a radar source, navigate the UAV to the source efficiently using 
on-board sensor measurements, and circle around the emitter. We 
successfully tested an evolved UAV controller on a wheeled mobile robot. A 
passive sonar system on the robot was used in place of the radar sensor, 
and a speaker emitting a tone was used as the target in place of a radar. 
Using the evolved navigation controller, the mobile robot moved to the 
speaker and circled around it. The results from this experiment 
demonstrate that our evolved controllers are capable of transference to 
real vehicles. Future research will include testing the best evolved 
controllers by using them to fly real UAVs.