Autonomous Agents for Real-time Animation

Advances in computing hardware, software, and network technology have enabled a new class of interactive applications involving 3D animated characters to become increasingly feasible. Many such applications require algorithms that allow both autonomous and user-controlled animated human figures to move naturally and realistically in response to task-level commands. This thesis presents a research framework aimed at facilitating the high-level control of animated characters in real-time virtual environments. The framework design is inspired by research in motion planning, control, and sensing for autonomous mobile robots. In particular, the problem of synthesizing motions for animated characters is approached from the standpoint of modelling and controlling a “virtual robot”. Two important classes of task-level motion control are investigated in detail. First, a technique for quickly synthesizing from navigation goals the collision-free motions for animated human figures in dynamic virtual environments is presented. The method combines a fast 2D path planner, a path-following controller, and cyclic motion capture data to generate the underlying animation. The rendering hardware is used to simulate the visual perception of a character, providing a feedback loop to the overall navigation strategy. Second, a method for automatically generating collision-free human arm motions to complete high-level object grasping and manipulation tasks is formulated. Given a target position and orientation in the workspace, a goal configuration for the arm is computed using an inverse kinematics algorithm that attempts to select a collision-free, natural posture. If successful, a randomized path planner is invoked to search the configuration space (C-space) of the arm, modeled as a kinematic chain with seven degrees of freedom (DOF), for a collision-free path