This paper presents a 50-d.o.f. humanoid robot, Computational Brain (CB). CB is a humanoid robot created for exploring the underlying processing of the human brain while dealing with the real world. We place our investigations within real-world contexts, as humans do. In so doing, we focus on utilizing a system that is closer to humans-in sensing, kinematics configuration and performance. We present the real-time network-based architecture for the control of all 50 d.o.f. The controller provides full position/velocity/force sensing and control at 1 kHz, allowing us the flexibility in deriving various forms of control. A dynamic simulator is also presented; the simulator acts as a realistic testbed for our controllers and acts as a common interface to our humanoid robots. A contact model developed to allow better validation of our controllers prior to final testing on the physical robot is also presented. Three aspects of the system are highlighted in this paper: (i) physical power for walking, (ii) full-body compliant control-physical interactions and (iii) perception and control-visual ocular-motor responses.

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This paper presents a 50-d.o.f. humanoid robot, Computational Brain (CB). CB is a humanoid robot created for exploring the underlying processing of the human brain while dealing with the real world. We place our investigations within real-world contexts, as humans do. In so doing, we focus on utilizing a system that is closer to humans-in sensing, kinematics configuration and performance. We present the real-time network-based architecture for the control of all 50 d.o.f. The controller provides full position/velocity/force sensing and control at 1 kHz, allowing us the flexibility in deriving various forms of control. A dynamic simulator is also presented; the simulator acts as a realistic testbed for our controllers and acts as a common interface to our humanoid robots. A contact model developed to allow better validation of our controllers prior to final testing on the physical robot is also presented. Three aspects of the system are highlighted in this paper: (i) physical power for walking, (ii) full-body compliant control-physical interactions and (iii) perception and control-visual ocular-motor responses.

We show that a humanoid robot can step and walk using simple sinusoidal desired joint trajectories with their phase adjusted by a coupled oscillator model. We use the center of pressure location and velocity to detect the phase of the lateral robot dynamics. This phase information is used to modulate the desired joint trajectories. We applied the proposed control approach to our newly developed human sized humanoid robot and a small size humanoid robot developed by Sony, enabling them to generate successful stepping and walking patterns.

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This paper proposes a passivity-based hierarchical full-body motion controller for force-controllable multi-DOF humanoid robots. The task-space forces are treated in a uniform manner for a variety of position/force tracking and force/moment compensation. The contact force closure is optimally solved and transformed directly into the joint torques in real-time without any joint trajectory planning. With this framework, we introduce gravity compensation at the lowest layer of the controller that makes the closed-loop system passive with respect to additional inputs as well as external forces. Furthermore, we propose two upper-layers: one layer controls the ground reaction forces, which enables the robot keep the dynamic balance. The other layer is the another passification control, which constructs an invariant manifold that prevents the robot from falling during walking. Four realistic dynamic simulations: balanced squatting, reaching, externally driven, or speed-controlled walking with disturbances demonstrate the effectiveness of the proposed methods.

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