Control of variable speed gaits for a biped robot

We discuss a balance scheme for handling variable-speed gaits that was implemented on an experimental biped at the University of New Hampshire. The control scheme uses preplanned but adaptive motion sequences in combination with closed-loop reactive control. CMAC neural networks are responsible for the adaptive control of side-to-side and front-to-back balance. The biped is able to walk with variable-speed gaits and to change gait speeds on the fly. The slower gait speeds require statically balanced walking, while the faster speeds require dynamically balanced walking. It is not necessary to distinguish between the two balance modes within the controller. Following training, the biped is able to walk on flat, nonslippery surfaces at forward velocities in the range of 21 cm/min to 72 cm/min, with an average stride length of 6.5 cm