A Hybrid CPG–ZMP Controller for the Real-Time Balance of a Simulated Flexible Spine Humanoid Robot

Although a few researchers have started to realize the importance of a flexible spine in generating more natural-looking behaviors for humanoid robots, there has been no work on trying to make a full-body humanoid robot (that has a flexible spine) to maintain balance. The main reason for this is that it is very costly and difficult to develop and control this kind of robot. This paper serves two purposes. First, it proposes the use of a realistic 3-D robot simulator as a platform for costly flexible spine humanoid robotics research. Second, it presents a hybrid CPG-ZMP controller for the simulated robot. The biologically inspired CPG component of our controller allows the mechanical spine and feet to exhibit rhythmic motions using only two control parameters. Through monitoring the measured ZMP location, the engineering component modulates the neural activity of the CPG to allow the robot to maintain balance while it is standing and exhibiting motions on the sagittal and frontal planes in real time. The final postures of the simulated humanoid emerge automatically in real time through dynamic interactions between the neural networks, the robot itself, and its environment. Since experimental results have also demonstrated that our system is robust against disturbances from external pushing forces, our controller has the potential to be applicable to the next generation of humanoid robots.