This paper outlines a new developmental approach to motor learning in very high-dimensions, applied to learning biped locomotion in humanoid robots. This approach relies on the formal modeling and coupling of several advanced mechanisms for actively controlling the growth of complexity and harnessing the curse of dimensionality: 1) Adaptive, multi-objective and staged fitness functions; 2) Maturational constraints for the progressive release of new degrees of freedoms; 3) Artificial curiosity; 4) Motor synergies; 5) Morphological computation. An experimental setup involving both the Acroban humanoid robot and a simulated version of the robot is presented.