3D cameras have emerged as a critical source of information for applications
in robotics and autonomous driving. These cameras provide robots with the
ability to capture and utilize point clouds, enabling them to navigate their
surroundings and avoid collisions with other objects. However, current standard
camera evaluation metrics often fail to consider the specific application
context. These metrics typically focus on measures like Chamfer distance (CD)
or Earth Mover's Distance (EMD), which may not directly translate to
performance in real-world scenarios. To address this limitation, we propose a
novel metric for point cloud evaluation, specifically designed to assess the
suitability of 3D cameras for the critical task of collision avoidance. This
metric incorporates application-specific considerations and provides a more
accurate measure of a camera's effectiveness in ensuring safe robot navigation.

为了解决当前标准相机评估指标无法准确考虑应用上下文的问题，我们提出了一种新的用于评估点云的度量标准，该度量标准专门设计用于评估 3D 相机在关键的避碰任务中的适用性，并结合应用特定的考虑因素来提供一个更准确的评估控制机器人安全导航性能的度量标准。