We present a novel control algorithm for simulating an articulated character performing a given reference motion and its variations. The unique feature of our controller is its ability to make a long-horizon plan at every time step. Our algorithm overcomes the computational hurdle by applying modal analysis on a time-varying linear dynamic system. We exploit the properties of modal coordinates in two ways. First, we design separate control strategies for dynamically decoupled modes. Second, our controller only applies long-horizon planning on a subset of modes, largely reducing the size of the control problem. With this decoupled and reduced control system, the character is able to execute the reference motion while reacting to unexpected perturbations and anticipating changes in the environment. We demonstrate our results by simulating a variety of reference motions, such as walking, squatting, jumping, and swinging.

In this paper, we investigate the impact of the deformable bodies on the control algorithms for physically simulated characters. We hypothesize that ignoring the effect of deformable bodies at the site of contact negatively affects the control algorithms, leading to less robust and unnatural character motions. To verify the hypothesis, we introduce a compact representation for an articulated character with deformable soft tissue and develop a practical system to simulate two-way coupling between rigid and deformable bodies in a robust and efficient manner. We then apply a few simple and widely used control algorithms, such as pose-space tracking control, Cartesian-space tracking control, and a biped controller (SIMBICON), to simulate a variety of behaviors for both full-body locomotion and hand manipulation. We conduct a series of experiments to compare our results with the motion generated by these algorithms on a character comprising only rigid bodies. The evaluation shows that the character with soft contact can withstand larger perturbations in a more noisy environment, as well as produce more realistic motion.

We present a physics-based approach to synthesizing motion of a virtual character in a dynamically varying environment. Our approach views the motion of a responsive virtual character as a sequence of solutions to the constrained optimization problem formulated at every time step. This framework allows the programmer to specify active control strategies using intuitive kinematic goals, significantly reducing the engineering effort entailed in active body control. Our optimization framework can incorporate changes in the character's surroundings through a synthetic visual sensory system and create significantly different motions in response to varying environmental stimuli. Our results show that our approach is general enough to encompass a wide variety of highly interactive motions.