Ricerc@Sapienza

The ability to build maps is a key functionality for the majority of mobile robots. A central ingredient to most mapping systems is the registration or alignment of the recorded sensor data. In this paper, we present a general methodology for photometric registration that can deal with multiple different cues. We provide examples for registering RGBD as well as 3D LIDAR data. In contrast to popular point cloud registration approaches such as ICP our method does not rely on explicit data association and exploits multiple modalities such as raw range and image data streams.

Commodity HardWare (CHW) is currently used in the Internet to deploy large data centers or small computing nodes. Moreover, CHW will be also used to deploy future telecommunication networks, thanks to the adoption of the forthcoming network softwarization paradigm. In this context, CHW machines can be put in Active Mode (AM) or in Sleep Mode (SM) several times per day, based on the traffic requirements from users. However, the transitions between the power states may introduce fatigue effects, which may increase the CHW maintenance costs.

The internal inspection of large pipeline infrastructures, such as sewers and waterworks, is a fundamental task for the prevention of possible failures. In particular, visual inspection is typically performed by human operators on the basis of video sequences either acquired on-line or recorded for further off-line analysis. In this work, we propose a vision-based software approach to assist the human operator by conveniently showing the acquired data and by automatically detecting and highlighting the pipeline sections where relevant anomalies could occur.