计算机肌肉建模中的碰撞检测与响应方法

Ondřej Havlíček, M. Cervenka, J. Kohout
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摘要

计算机肌肉建模用于许多目的,从损伤恢复和慢性疾病的治疗到疾病预测。这些预测通常涉及计算肌肉的内力,以进一步确定事情可能发生的速度(例如,肌肉关节磨损的速度)。在该模型的仿真过程中,不可避免地会发生软体和刚体的碰撞。本文测试了各种最先进的碰撞处理方法:体素化,一种使用Signed Distance Fields,另一种基于Bounding Volume Hierarchies。这些方法在肌肉建模的背景下与先前提出的基于位置的动力学方法进行了测试。与其他选项相比,使用Discregrid库生成Signed Distance Field显示出最好的结果,主要是由于它的准确性与执行速度的比率。与目前的系统相比,视觉愉悦的改进是显著的。
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Collision detection and response approaches for computer muscle modelling
Computer muscle modelling is used for many pur-poses, from injury recovery and treatment of chronic diseases to disease prediction. These predictions often involve computing the muscle's internal forces to determine further how fast something may happen (e.g. how quickly the muscle joint wears out). During the simulation of such a model, collisions of soft and rigid bodies inevitably occur. This paper tests various state-of-the-art collision handling methods: voxelisation, one using Signed Distance Fields and one based on Bounding Volume Hierarchies. These methods are tested in the context of muscle modelling with the previously proposed position-based dynamics approach. Compared to the other options, using the Discregrid library for Signed Distance Field generation shows the best results, mainly due to its accuracy to the speed of execution ratio. In contrast to the current system, visually pleasant improvements are significant.
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