Point cloud culling for robot vision tasks under communication constraints

In this paper, we present two real-time methods for controlling data transmission in a robotic network that utilizes a remote computing infrastructure. The proposed algorithms use information and communication theory concepts to perform a highly efficient transfer of RGB-D data from a client (robot) to a server (cloud). We show that this approach makes it possible to conserve bandwidth and reduce network latency while allowing a mobile robot to perform vision tasks.