OptiTrap：用于声悬浮显示器的最优陷阱轨迹
OptiTrap: Optimal Trap Trajectories for Acoustic Levitation Displays
AI总结：
提出首个结构化数值方法 OptiTrap，通过多维声力模型和非线性路径跟随求解，生成物理可行且时间最优的声悬浮陷阱轨迹，实现更大更复杂的半空中形状渲染。
摘要：
声悬浮最近展示了通过捕获粒子并使其沿参考路径快速移动以在半空中显现形状，从而创建体积内容的能力。然而，指定物理可行的陷阱轨迹来显示所需形状的问题仍未解决。即使内容创作者只对最终形状感兴趣，陷阱轨迹也需要确定陷阱在何时何地出现，以便粒子显现预期的形状。我们提出了 OptiTrap，这是首个用于计算声悬浮显示器陷阱轨迹的结构化数值方法。我们的方法生成物理可行且几乎时间最优的陷阱轨迹，仅需给定参考路径（即无时间信息的形状），即可显现通用的半空中形状。我们提供了陷阱周围声力的多维模型，以建模陷阱-粒子系统动力学，并通过构建和求解非线性路径跟随问题来计算最优陷阱轨迹。我们构建了该方法并进行了评估，展示了 OptiTrap 如何持续生成可行且接近最优的路径，提高了渲染形状的尺寸、频率和准确性，使我们能够展示比以往更大、更复杂的形状。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
