Automatic Controller Selection on a Humanoid Robot: Using Optimization Techniques

Designing controllers for complex robots is not an easy task. Often, researchers hand-tune controllers for humanoid robots, but this is a time-consuming approach that yields a single controller which cannot generalize well to varied tasks. This thesis presents a method which uses the NSGA-II multi-objective optimization (MOO) algorithm with...