Geometry-Based Muscle Forces and Inverse Dynamics for Animation

摘要

In this paper, we present an animation technique based on muscle forces, inverse dynamics and a parameter optimization. We do a crude motion planning in terms of accelerations. By integrating the accelerations given an initial configuration, we obtain all essential kinematic data. We evaluate the quality of motion planning by using various constraints and a performance index evaluated using inverse dynamics. The best motion can be chosen by using a parameter optimization method. The human motion is so complicated that it needs the motions to be coordinated nicely. The planned motion is checked using a criterion which we call the footprint function: ground reaction forces if the body is on the ground, acceleration of the body center as well as energy if it is in the air. In the motion planning for a body in the air, we reduce control variables so that we work with a smaller search space with only feasible motions. Then we include human skeletal and muscle geometry in the footprint function so that we can convert robotic rotary actuators to muscles using static optimization: given a set of joint torques, we distribute them to the eight sets of human low extremity muscles. We search most human-like animated motion from an infinite set of possible motions. We compare these with experimental data. Futhermore, the muscle geometric data obtained from our linear actuator modeling can be used in tissue animation.