Simulation of spatial human walking is a challenging problem from analytical and computational points of view. A new methodology, called predictive dynamics, is introduced in this work to simulate human walking using a spatial digital human model.;The digital human model has 55 degrees of freedom, 6 degrees of freedom for global translation and rotation and 49 degrees of freedom representing the kinematics of the body. The resultant action of all the muscles at a joint is lumped and represented by the torque at each degree of freedom. In addition, the cubic B-spline interpolation is used for time discretization and the well-established robotic formulation of the Denavit-Hartenberg (DH) method is used for kinematics analysis of the mechanical system. The recursive Lagrangian formulation is used to develop the equations of motion, and is chosen because of its known computational efficiency. The approach is also suitable for evaluation of the gradients in closed form that are needed in the optimization process. Furthermore, dynamic stability, the zero moment point (ZMP) location, is calculated from equations of motion with analytical gradients. The ground reaction forces (GRF) are obtained from a novel two-step active-passive algorithm. The problem is formulated as a nonlinear optimization problem. A unique feature of the formulation is that the equations of motion are not integrated explicitly, but evaluated by inverse dynamics in the optimization process to enforce the laws of physics, thus the optimal solution is obtained in a short time. Three walking formulations are discussed: (1) one-step walking formulation, (2) one-stride walking formulation, and (3) minimum-time walking formulation. A program based on a sequential quadratic programming (SQP) approach is used to solve the nonlinear optimization problem.;Besides normal walking, several other cases are also considered, such as walking with a shoulder backpack of varying loads, walking at different speed, walking with asymmetric step lengths, and walking with reduced torque limits. In addition to the kinematics data, kinetics data such as joint torques and ground reaction forces are recovered from the simulation and some insights are obtained for the pathological gait.
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