LAUSR

In robotic teleoperation, the knowledge of the state of the remote environment in real time is paramount. Advances in the development of highly accurate 3D cameras able to provide high-quality point clouds appear to be a feasible solution for generating live, up-to-date virtual environments. Unfortunately, the exceptional accuracy and high density of these data represent a burden for communications requiring a large bandwidth affecting setups where the local and remote systems are particularly geographically distant. This paper presents a multiple level-of-detail (LoD) compression strategy for 3D data based on tree-like codification structures capable of compressing a single data frame at multiple resolutions using dynamically configured parameters. The level of compression (resolution) of objects is prioritised based on: (i) placement on the scene; and (ii) the type of object. For the former, classical point cloud fitting and segmentation techniques are implemented; for the latter, user-defined prioritisation is considered. The results obtained are compared using a single LoD (whole-scene) compression technique previously proposed by the authors. Results showed a considerable improvement to the transmitted data size and updated frame rate while maintaining low distortion after decompression.