Hardware-ased parallel computing tools for realtime haptic and deformation rendering of soft objects

交互式虚拟现实模拟器通过结合视觉、动觉和力反馈（也称为触觉）等传感模式，正变得越来越逼真。与非刚性可变形物体的相互作用经常发生在涉及生物软组织的医学应用中。虽然在这些相互作用的基于物理的数学建模方面取得了很大的进展，但这些模型在实时模拟中的实际应用仍然有限，主要是由于它们的计算复杂性。特别是，具有触觉反馈的应用将需要非常高的仿真更新速率来保持系统稳定性，这对现有单处理器计算机的能力施加了严格的时间限制。基于我们之前在触觉方面的工作，本研究探索了一种新的并行计算范式，用于涉及视觉和触觉反馈的软物体交互的实时高保真仿真。定制的计算工具将被开发，同时使用数千个处理单元来解决由软物体变形的有限元模型产生的大型稀疏方程组。该解决方案将以足够高的更新率获得仿真稳定性和保真度。这些计算工具本质上是使用现场可编程门阵列（FPGA）技术在合成硬件架构上并行实现递归方程求解器。在多个相互连接的FPGA芯片上的大规模并行计算将以廉价和紧凑的封装提供巨大的计算能力，从而实现高保真软组织变形模型的模拟。这项研究的结果将有助于下一代计算机辅助手术系统和医疗训练模拟器的发展。将由此产生的核心计算技术集成到这些系统中，将在计算机辅助医疗培训、诊断以及医疗干预的规划和执行方面创造改进的和新的操作能力。其他需要快速求解稀疏线性方程组的科学应用也将受益于这项研究。

Interactive virtual reality simulators are becoming increasingly realistic by incorporating sensing modalities such as vision, kinesthesia and force feedback, also known as haptics. Interactions with non-rigid deformable objects often occur in medical applications involving biological soft-tissue. While a great deal of progress has been made in physics-based mathematical modeling of these interactions, practical applications of such models in real-time simulations have remained limited mainly due to their computational complexity. In particular, applications with haptic feedback would require very high simulation update rates to maintain the system stability, imposing strict timing constraints beyond the capabilities of existing single-processor computers. Building upon our previous work in haptics, this research explores a new paradigm in parallel computing for real-time high-fidelity simulation of soft-object interaction involving visual and haptic feedback. Customized computing tools will be developed that concurrently employ thousands of processing units to solve a large sparse system of equations arising from the finite element models of soft-object deformation. The solution will be obtained at sufficiently high update rates for simulation stability and fidelity. These computing tools will be essentially parallel implementations of recursive equation solvers on synthesized hardware architectures using the Field-Programmable Gate Array (FPGA) technology. Massive parallelization of the computations on multiple interconnected FPGA chips will provide enormous computing power in an inexpensive and compact package enabling the simulation of high-fidelity soft-tissue deformation models. The results of this research will be instrumental in the development of the next generation of computer-assisted surgical systems and medical training simulators. The integration of the resulting core computational technologies into such systems will create improved and new operational capabilities in computer-assisted medical training, diagnosis, and planning and execution of medical interventions. Other scientific applications requiring fast solutions to sparse linear systems of equations will also benefit from this research.