Generating effective whole-body motions of a human-like mechanism with efficient ZMP formulation

An optimization-based methodology of generating dynamic biped motions of a human-like mechanism is proposed. An efficient formulation of the zero-moment point (ZMP) for dynamic balance and the ground reaction loads is derived from the resultant reaction loads, which includes the gravity, the applied loads, and the inertia. The optimization problem is formulated to address the redundancy subject to the general biped and task-specific constraints. The proposed method is fully predictive and generates physically feasible human-like motions from scratch without input reference. The generated motions demonstrate how a human-like mechanism reacts effectively to different external load conditions by showing realistic features of causes and effects. In addition, the energy-optimality of the upright biped standing posture is numerically verified.