Robotic Locomotion combining Central Pattern Generators and Reflexes

The development of bio-inspired controllers seems to be a good and robust way to obtain an efficient and robust robotic locomotion, mimicking their biological counterparts. In this Master Thesis two bio-inspired controllers were developed in order to generate stable and robust locomotion on uneven terrains. Firstly, a reflex controller that has to be capable of generating locomotion, based only on sensory information. Secondly, a hybrid controller that combines Central Pattern Generators (CPGs) and reflexes. The results show that the reflex controller is capable of producing stable quadruped locomotion with a regular stepping pattern, and it proved to be capable of dealing with slopes and small obstacles. The hybrid controller improved the robot's behavior by increasing its stability, harmony and displacement in the majority of the experiments. Moreover, the stepping patterns become more regular. This combination enables to increase robustness to sensor imperfections and to anticipate the robot's motor actions.