This paper presents a method and algorithms for automatic modeling of anatomical joint motion. The method relies on collision detection to achieve stable positions and orientations of the knee joint by evaluating the relative motion of the tibia with respect to the femur (for example, flexion-extension). The stable positions then become the basis for a look-up table employed in the animation of the joint. The strength of this method lies in its robustness to animate any normal anatomical joint. It is also expandable to other anatomical joints given a set of kinematic constraints for the joint type as well as a high-resolution, static, 3-D model of the joint. The demonstration could be patient specific if a person's real anatomical data could be obtained from a medical imaging modality such as computed tomography or magnetic resonance imaging. Otherwise, the demonstration requires the scaling of a generic joint based on patient characteristics. Compared with current teaching strategies, this Virtual Reality Dynamic Anatomy (VRDA) tool aims to greatly enhance students' understanding of 3-D human anatomy and joint motions. A preliminary demonstration of the optical superimposition of a generic knee joint on a leg model is shown.