论文标题
OptitRap:用于声悬浮显示的最佳陷阱轨迹
OptiTrap: Optimal Trap Trajectories for Acoustic Levitation Displays
论文作者
论文摘要
声音悬浮最近证明了通过捕获和快速移动粒子沿参考路径以揭示空气中的形状来创建体积含量的能力。但是,指定出现物理可行的陷阱轨迹以显示所需形状的问题尚未解决。即使内容创建者只有最终形状是感兴趣的,陷阱轨迹也需要确定陷阱需要何时和何时需要,以使粒子揭示预期的形状。我们提出了OptitRap,这是用于计算陷阱轨迹的第一种结构化数值方法。我们的方法生成了物理上可行且几乎最佳时间的陷阱轨迹,并揭示了通用的中空形状,只有一个参考路径(即,没有时间信息的形状)。我们通过陷阱围绕陷阱的声力提供多维模型,以模拟陷阱粒子系统动力学,并通过对问题进行制定和解决非线性路径来计算最佳的陷阱轨迹。我们制定了方法并评估它,展示了亮片如何始终如一地产生可行且几乎最佳的路径,并且形状的尺寸,频率和精度增加,从而使我们能够比迄今为止所显示的更大,更复杂的形状。
Acoustic levitation has recently demonstrated the ability to create volumetric content by trapping and quickly moving particles along reference paths to reveal shapes in mid-air. However, the problem of specifying physically feasible trap trajectories to display desired shapes remains unsolved. Even if only the final shape is of interest to the content creator, the trap trajectories need to determine where and when the traps need to be, for the particle to reveal the intended shape. We propose OptiTrap, the first structured numerical approach to compute trap trajectories for acoustic levitation displays. Our approach generates trap trajectories that are physically feasible and nearly time-optimal, and reveal generic mid-air shapes, given only a reference path (i.e., a shape with no time information). We provide a multi-dimensional model of the acoustic forces around a trap to model the trap-particle system dynamics and compute optimal trap trajectories by formulating and solving a non-linear path following problem. We formulate our approach and evaluate it, demonstrating how OptiTrap consistently produces feasible and nearly optimal paths, with increases in size, frequency, and accuracy of the shapes rendered, allowing us to demonstrate larger and more complex shapes than ever shown to date.