[HTML][HTML] Perspectives of realsense and zed depth sensors for robotic vision applications

V Tadic, A Toth, Z Vizvari, M Klincsik, Z Sari, P Sarcevic… - Machines, 2022 - mdpi.com
This review paper presents an overview of depth cameras. Our goal is to describe the
features and capabilities of the introduced depth sensors in order to determine their …

A dynamic clustering algorithm for lidar obstacle detection of autonomous driving system

F Gao, C Li, B Zhang - IEEE Sensors Journal, 2021 - ieeexplore.ieee.org
Lidar is an important sensor of the autonomous driving system to detect environmental
obstacles, but the spatial distribution of its point cloud is non-uniform because of the …

A traffic data clustering framework based on fog computing for VANETs

MLM Peixoto, AHO Maia, E Mota, E Rangel… - Vehicular …, 2021 - Elsevier
Abstract Vehicular Ad-hoc Networks (VANETs) are based on vehicle to infrastructure
communications in which the vehicles periodically broadcast information to update a Road …

Ananke: a streaming framework for live forward provenance

D Palyvos-Giannas, B Havers… - Proceedings of the …, 2020 - dl.acm.org
Data streaming enables online monitoring of large and continuous event streams in Cyber-
Physical Systems (CPSs). In such scenarios, fine-grained backward provenance tools can …

Painting path planning for a painting robot with a realsense depth sensor

V Tadic, A Odry, E Burkus, I Kecskes, Z Kiraly… - Applied Sciences, 2021 - mdpi.com
The utilization of stereo cameras in robotic applications is presented in this paper. The use
of a stereo depth sensor is a principal step in robotics applications, since it is the first step in …

Driven: a framework for efficient data retrieval and clustering in vehicular networks

B Havers, R Duvignau, H Najdataei… - 2019 IEEE 35th …, 2019 - ieeexplore.ieee.org
Applications for adaptive (sometimes also called smart) Cyber-Physical Systems are
blossoming thanks to the large volumes of data, sensed in a continuous fashion, in large …

DRIVEN: A framework for efficient Data Retrieval and clustering in Vehicular Networks

B Havers, R Duvignau, H Najdataei, V Gulisano… - Future Generation …, 2020 - Elsevier
The growing interest in data analysis applications for Cyber–Physical Systems stems from
the large amounts of data such large distributed systems sense in a continuous fashion. A …

Intelligent detection for tunnel shotcrete spray using deep learning and LiDAR

L Chun-Lei, S Hao, L Chun-Lai, L **-Yang - IEEE Access, 2019 - ieeexplore.ieee.org
Shotcrete spray is an indispensable process in tunnel construction. At present, the
construction of tunnels in China is mainly depend on labor or mobile concrete sprayer …

Towards data-driven additive manufacturing processes

V Gulisano, M Papatriantafilou, Z Chen… - Proceedings of the 23rd …, 2022 - dl.acm.org
Additive Manufacturing (AM), or 3D printing, is a potential game-changer in medical and
aerospatial sectors, among others. AM enables rapid prototy** (allowing development …

Mad-c: Multi-stage approximate distributed cluster-combining for obstacle detection and localization

A Keramatian, V Gulisano, M Papatriantafilou… - Journal of Parallel and …, 2021 - Elsevier
The upcoming digitalization in the context of Cyber–physical Systems (CPS), enabled
through Internet-of-Things (IoT) infrastructures, require efficient methods for distributed …