Model-based and model-free approaches for postural control of a compliant humanoid robot using optical flow

Abstract

Abstract-Vision is a very rich sensor with a proven critical role in the control of balance. However, it is widely underused for robotics postural control. This paper presents and compares two approaches, one model-based and one model-free, to ensure stability of the COMAN compliant humanoid robot standing on a moving platform. The model-based approach uses inverse kinematics, while the model-free one relies on a neural network as mapping between sensors and actuators. The sensory information is composed of proprioceptive cues (gyroscope) and visual cues, used separately or together. We present methods of using vision as sensory input without relying on a particular object or feature of the scene, but only on the optical flow. The performance of both approaches are compared systematically in a realistic robotics simulator, for different movements of the platform and using different sensory cues. We aim to see if vision can replace proprioceptive sensors or be fused with them to improve the performance of the stabilizing controller. While both model-based and model-free approaches successfully stabilize the robot, the model-free approach shows better overall performance. Preliminary results on the real COMAN robot are shown.

fNIRS-based Neurorobotic Interface for gait rehabilitation

“…Moreover, the base was assumed fixed, making it two serial-link manipulators in which one manipulator is moved 180° out of phase with the other one [ 61 – 64 ]. The average thigh clearance given in the literature for a man is 0.78 in, and for women, 0.90 in [ 65 , 66 ]. The end-effector position and orientation were derived from the Denavit-Hartenberg (D-H) notation [ 57 , 59 , 67 , 68 ].…”

“…In the present study, prosthetic leg simulations were performed with different stride lengths given by the National Center for Health Statistics [ 65 , 66 ]. Figure 8 shows a simulation plot of the biped robot at different instants.…”

Real-time full body motion imitation on the COMAN humanoid robot

“…The emphasis of the paper was on the control with respect to external impacts. A model-free approach, completely excluding the kinematics, was used for postural control of the same compliant robotic platform by Gay et al 19 In their approach, the authors used visual flow and gyroscopes as the input into optimized neural networks. In our paper, we show how we can perform postural control and motion imitation online, without of-line optimization.…”