A hybrid CPG–ZMP control system for stable walking of a simulated flexible spine humanoid robot

Biped humanoid robots have gained much popularity in recent years. These robots are mainly controlled by two major control methods, the biologically-inspired approach based on Central Pattern Generator (CPG) and the engineering-oriented approach based on Zero Moment Point (ZMP). Given that flexibility in the body torso is required in some human activities, we believe that it is beneficial for the next generation of humanoid robots to have a flexible spine as humans do. In order to cope with the increased complexity in controlling this type of robot, a new kind of control system is necessary. Currently, there is no controller that allows a flexible spine humanoid robot to maintain stability in real-time while walking with dynamic spine motions. This paper presents a new hybrid CPG–ZMP control system for the walking of a realistically simulated flexible spine humanoid robot. Experimental results showed that using our control method, the robot is able to adapt its spine motions in real-time to allow stable walking. Our control system could be used for the control of the next generation humanoid robots.