This research work focuses on developing a Bio-inspired Behavior-Based Bipedal Locomotion Control (B4LC) for bipeds relying heavily on the transfer of concepts found in the locomotion control of humans. Based on a thorough review on biomechanics and neuroscience literature, a control approach is derived that can achieve dynamic, efficient, and robust walking of three-dimensional and fully articulated bipeds. Being located above the neural level, the control system is structured as a hierarchical network of local feed-forward and feedback units, without using a complete dynamic model or pre-calculated joint trajectories. Sensor event-based spinal pattern generators coordinate the stimulation and synchronization of control units and the compliance of passive joints.
The proposed approach is being tested in a full-featured dynamics simulation framework on an anthropomorphic biped with 21 degrees of freedom and human-like morphology, weight, and actuation. The control system can achieve three-dimensional dynamic walking of variable velocity as well as balanced standing. It is able to cope with the high complexity and the mechanical elasticities of the modeled biped. The emerging, naturally looking walking gait shows remarkable similarities to human walking. The achieved walking velocity of up to 5 km/h can compete with even the most advanced of today's bipeds. The control system shows considerable robustness against unknown and unexpected disturbance like steps, slopes, or external forces.