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Velocity Estimation Algorithms for Audio-Haptic Simulations Involving Stick-Slip

机译:涉及粘滑的声频仿真的速度估计算法

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摘要

With real-time models of friction that take velocity as input, accuracy depends in great part on adequately estimating velocity from position measurements. This process can be sensitive to noise, especially at high sampling rates. In audio-haptic acoustic simulations, often characterized by friction-induced, relaxation-type stick-slip oscillations, this gives a gritty, dry haptic feel and a raspy, unnatural sound. Numerous techniques have been proposed, but each depend on tuning parameters so that they may offer a good trade-off between delay and noise rejection. In an effort to compare fairly, each of thirteen methods considered in the present study was automatically optimized and evaluated; finally a subset of these were compared subjectively. Results suggest that no one method is ideal for all gain levels, though the best general performance was found by using a sliding-mode differentiator as input to a Kalman integrator. An additional conclusion is that estimators do not approach the quality available in physical velocity transduction, and therefore such sensors should be considered in haptic device design.
机译:对于以速度为输入的实时摩擦模型,精度很大程度上取决于从位置测量中适当估计速度。此过程可能对噪声敏感,尤其是在高采样率的情况下。在音频触觉声学模拟中,通常以摩擦引起的松弛型粘滑振荡为特征,这会产生沙粒状,干燥的触觉,并产生刺耳的,不自然的声音。已经提出了许多技术,但是每种技术都取决于调整参数,因此它们可以在延迟和噪声抑制之间提供良好的折衷。为了公平地进行比较,本研究中考虑的13种方法中的每一种均被自动优化和评估。最后,将其中的一部分进行主观比较。结果表明,没有一种方法适合所有增益水平,尽管通过使用滑模微分器作为卡尔曼积分器的输入可以找到最佳的总体性能。另一个结论是,估计器无法达到物理速度转换中可用的质量,因此在触觉设备设计中应考虑此类传感器。

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