Blending Collision Avoidance Animation in Synthetically Generated Locomotion
PubDate: November 2021
Teams: University of Patra
Writers: Konstantinos Kalatzis; Konstantinos Moustakas
Recent techniques of deep supervised learning have shown success in the domain of locomotion, providing high-quality and very realistic results. However, extending these systems to support further animation possibilities, with the character adapting to its environment and interacting with objects on a scene remains a challenging task. Manually specifying key frames to produce motion for individual interactions, can be a tedious and expensive task. In this paper, an inverse kinematic approach is discussed for collision avoidance with objects, as a way for extending the animation capabilities of characters. The system is based on the FABRIK algorithm in Unity3D for collision avoidance with objects of different sizes and geometry. The scalability of the system is demonstrated as it works with both quadruped and biped characters in real-time.