Abstract
AbstractThis paper reviews modern geometrical dynamics and control of humanoid robots. This general Lagrangian and Hamiltonian formalism starts with a proper definition of humanoid's configuration manifold, which is a set of all robot's active joint angles. Based on the ‘covariant force law’, the general humanoid's dynamics and control are developed. Autonomous Lagrangian dynamics is formulated on the associated ‘humanoid velocity phase space’, while autonomous Hamiltonian dynamics is formulated on the associated ‘humanoid momentum phase space’. Neural-like hierarchical humanoid control naturally follows this geometrical prescription. This purely rotational and autonomous dynamics and control is then generalized into the framework of modern non-autonomous biomechanics, defining the Hamiltonian fitness function. The paper concludes with several simulation examples.
Highlights
Humanoid robots, being the future of robotic science, are becoming more and more human-like in all aspects of their functioning. Both human biodynamics and humanoid robotics are governed by Newtonian dynamical laws and reflex−like nonlinear controls [1, 2, 8, 10, 11]
Within the realm of rigid body mechanics, a segment of a human arm or leg is not properly represented as a rigid body fixed at a certain point, but rather as a rigid body hanging on rope−like ligaments
We develop the autonomous Hamiltonian robotics on humanoid's configuration manifold Mrob = M in three steps, following the standard symplectic geometry prescription: Step A Find a symplectic momentum phase−space (P, ω)
Summary
Humanoid robots, being the future of robotic science, are becoming more and more human-like in all aspects of their functioning. The whole skeleton mechanically represents a system of flexibly coupled rigid bodies, technically an anthropomorphic topological product of SE(3)−groups. This implies more complex kinematics, dynamics and control than in the case of humanoid robots [3]. In contrast to our previously published papers, the present article provides full technical details of both autonomous and nonautonomous (time-dependent) biodynamics and robotics, including the new neuro−muscular fitness dynamics. This thorough theoretical background would provide an interested reader with superb capability to develop their own non-autonomous humanoid simulator
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