Abstract: Provided is a full-body modeling method and apparatus based on new model predictive control (MPC) with a visuomotor system in which visual perception and full-body motion control are integrated. The full-body modeling method includes determining a partial observation value associated with a state of an object based on a point of sight of a character, estimating the state of the object using the determined partial observation value based on a partially observable Markov decision process (POMDP), controlling a state of the character based on the estimated state of the object, and visualizing a motion of the character.

Abstract: Provided is a full-body modeling method and apparatus based on new model predictive control (MPC) with a visuomotor system in which visual perception and full-body motion control are integrated. The full-body modeling method includes determining a partial observation value associated with a state of an object based on a point of sight of a character, estimating the state of the object using the determined partial observation value based on a partially observable Markov decision process (POMDP), controlling a state of the character based on the estimated state of the object, and visualizing a motion of the character.

Abstract: A method of simulating a motion of an object controlling another object based on an example motion or a previously generated motion of the object is disclosed. The method includes refining a motion of a first object based on a motion of the first object predicted based on a motion specification, and on a trajectory of a second object controlled by the first object, and simulating the motion of the first object and the trajectory of the second object based on a vector for controlling joints of the first object that is generated based on the refined motion.

Abstract: Disclosed is a model predictive control. The model predictive control method includes: receiving an input system dynamics model for a character; performing numerical differentiation to the input system dynamics model by using at least one technique selected from the group consisting of a differentiation information interpolation technique, a physical quantity reuse technique and a contact-space inverse mass matrix (CIMM) technique; and outputting differentiation information for the system dynamics model.