School of Mechanical Engineering, Hanoi University of Science and Technology, Hanoi, Vietnam.
Sci Prog. 2021 Jul-Sep;104(3):368504211036857. doi: 10.1177/00368504211036857.
Motion simulators are becoming increasingly popular for many applications in which human sensation is important to replicate and optimize target motions. For the emulation of the perceived human acceleration, motion cueing algorithms (MCAs) have been proposed in the literature that mimics the motion sensation by a combination of actual acceleration and tilted gravity effects, termed g-force or specific force. However, their relative performance has not yet been analyzed. This paper reviews existing families of MCAs and compares their performance for a simple offline S-shaped planar test trajectory featuring only lateral acceleration. The comparison is carried out both numerically using two previously published objective measures, the "performance indicator" of Pouliot, Gosselin, and Nahon, and the "good criterion" of Schmidt, as well as subjectively by a preliminary passenger rating on a real motion platform-Robocoaster testbed. The results show that (a) the novel optimizing MCA group exploits more effectively the workspace of the motion platform than the traditional MCA group for reducing false cue with small scale error and shape errors, (b) path-dependent tuning of MCA parameters may improve motion sensation, (c) average subjective ratings can be made to correlate well with the "good criterion" when expanded with a penalty for false angular velocity cues, and (d) the scale error of specific force seems to play the most important role to the evaluation of test subject on the motion cue quality. However, still a strong variance in subjective ratings was observed, making further research necessary.
运动模拟器在许多需要复制和优化目标运动的人类感觉的应用中变得越来越流行。为了模拟感知到的人体加速度，文献中提出了运动提示算法（MCAs），通过实际加速度和倾斜重力效应的组合来模拟运动感觉，称为重力加速度或比力。然而，它们的相对性能尚未得到分析。本文综述了现有的 MCA 族，并比较了它们在仅具有横向加速度的简单离线 S 形平面测试轨迹上的性能。比较是通过使用以前发布的两个客观指标，即 Pouliot、Gosselin 和 Nahon 的“性能指标”和 Schmidt 的“良好准则”进行数值计算，以及在真实运动平台-Robocoaster 试验台上进行初步的乘客评分进行主观评估。结果表明：（a）新型优化 MCA 组比传统 MCA 组更有效地利用运动平台的工作空间，以减少小尺度误差和形状误差的虚假提示；（b）MCA 参数的路径相关调优可以改善运动感觉；（c）当扩展到对错误角速度提示的惩罚时，平均主观评分可以很好地与“良好准则”相关联；（d）比力的尺度误差似乎对运动提示质量评估的测试对象具有最重要的作用。然而，仍然观察到主观评分的强烈差异，因此需要进一步研究。
