4916980
doi
10.1109/ACCESS.2021.3066529
oai:zenodo.org:4916980
user-eu
A. Gómez Eguíluz
GRVC Robotics Lab, University of Seville
J. R. Martínez-De Dios
GRVC Robotics Lab, University of Seville
A. Ollero
GRVC Robotics Lab, University of Seville
Auto-Tuned Event-Based Perception Scheme for Intrusion Monitoring With UAS
J. P. Rodríguez-Gómez
GRVC Robotics Lab, University of Seville
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
Event-based vision, intrusion detection, surveillance, UAV
<p>This paper presents an asynchronous event-based scheme for automatic intrusion monitoring using Unmanned Aerial Systems (UAS). Event cameras are neuromorphic sensors that capture the illumination changes in the camera pixels with high temporal resolution and dynamic range. In contrast to conventional frame-based cameras, they are naturally robust against motion blur and lighting conditions, which make them ideal for outdoor aerial robot applications. The presented scheme includes two main perception components. First, an asynchronous event-based processing system efficiently detects intrusions by combining several asynchronous event-based algorithms that exploit the advantages of the sequential nature of the event stream. The second is an off-line training mechanism that adjusts the parameters of the event-based algorithms to a particular surveillance scenario and mission. The proposed perception system was implemented in ROS for on-line execution on board UAS, integrated in an autonomous aerial robot architecture, and extensively validated in challenging scenarios with a wide variety of lighting conditions, including day and night experiments in pitch dark conditions.</p>
Zenodo
2021-03-17
info:eu-repo/semantics/article
4916979
user-eu
award_title=General compliant aerial Robotic manipulation system Integrating Fixed and Flapping wings to INcrease range and safety; award_number=788247; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/788247; funder_id=00k4n6c32; funder_name=European Commission;
award_title=AERIAL COgnitive integrated multi-task Robotic system with Extended operation range and safety; award_number=871479; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/871479; funder_id=00k4n6c32; funder_name=European Commission;
1625667831.733046
5956581
md5:90d4fca61b2f639e147bdbcf43727790
https://zenodo.org/records/4916980/files/IEEE_Access___2020.pdf
public
IEEE Access
9
44840 - 44854
2021-03-17