Blending Collision Avoidance Animation in Synthetically Generated Locomotion

Konstantinos Kalatzis, K. Moustakas
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Abstract

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.
混合合成生成运动中的避碰动画
最近的深度监督学习技术在运动领域取得了成功,提供了高质量和非常逼真的结果。然而,扩展这些系统以支持进一步的动画可能性,使角色适应其环境并与场景中的对象进行交互仍然是一项具有挑战性的任务。手动指定关键帧来为单个交互生成动作,可能是一项乏味且昂贵的任务。在本文中,讨论了一种逆运动学方法来避免与物体的碰撞,作为一种扩展角色动画能力的方法。该系统基于Unity3D中的FABRIK算法来避免不同尺寸和几何形状物体的碰撞。通过对四足和两足动物的实时处理,验证了该系统的可扩展性。
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