Real-time detection performance of RTSP vs. USB cameras for UGVs

bracu.type.groupResearch Publications
datacite.rightsMetadata Only
dc.contributor.authorSadman, Raheeb
dc.contributor.authorSafi, Safwan Sattar
dc.contributor.authorMahe, Jahedul Alam
dc.contributor.authorMaliha, Sabrina
dc.contributor.authorMashkura, Mahadia
dc.contributor.authorAli Sikder, Sajid
dc.contributor.authorAnan, Ahmad Ali Akand
dc.contributor.authorAbrar, Fahim
dc.contributor.departmentDepartment of Electrical and Electronic Engineering
dc.contributor.departmentDepartment of Computer Science and Engineering
dc.date.accessioned2026-09-16T10:42:47Z
dc.date.available2026-09-16T10:42:47Z
dc.date.issued2025-01-01
dc.description.abstractReal-time object detection is critical for ensuring the operational safety of unmanned ground vehicles (U G V s) in industrial inspection and last mile delivery applications, yet the impact of camera interface selection remains poorly understood. This study presents the first systematic comparison of USB web cams versus network cameras for UGV perception systems, focusing on safety critical scenarios including emergency braking and obstacle avoidance. Our experimen-tal results demonstrate that USB-based systems consistently outperform networked alternatives, offering superior frame processing efficiency, enhanced navigation precision during avoidance maneuvers, and significantly improved operational stability in prolonged deployments. These advantages are a result of USB's direct hardware interfacing and predictable low latency characteristics. The outcomes conclusively establish that for UGV applications, directly connected USB cameras provide more reliable vision performance, enabling robust collision avoidance in dynamic environments while maintaining exceptional tracking consistency and system robustness. Additionally, the study highlights the significant reduction in detection latency and jitter, which are important for real-time decision-making in fast-paced, safety in critical operations.
dc.description.versionPublished
dc.format.extent119-126
dc.identifier.citationR. Sadman et al., "Real-Time Detection Performance of RTSP vs. USB Cameras for UGVs," 2025 WRC Symposium on Advanced Robotics and Automation (WRC SARA), Beijing, China, 2025, pp. 119-126, doi: 10.1109/WRCSARA68202.2025.11194983.
dc.identifier.doi10.1109/WRCSARA68202.2025.11194983
dc.identifier.isbn9798331577940
dc.identifier.issn28353366
dc.identifier.other2-s2.0-105020909104
dc.identifier.urihttps://hdl.handle.net/10361/30010
dc.language.isoen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.
dc.relation.hasversion10.1109/WRCSARA68202.2025.11194983
dc.relation.ispartofProceeding of the Wrc Symposium on Advanced Robotics and Automation Wrc Sara
dc.relation.ispartofseriesProceeding of the Wrc Symposium on Advanced Robotics and Automation Wrc Sara
dc.relation.urihttps://ieeexplore.ieee.org/document/11194983
dc.rightsfalse
dc.subjectCamera interface comparison
dc.subjectMobile robotics
dc.subjectMotion detection
dc.subjectObject detection
dc.subjectReal time perception systems
dc.subjectRobot vision and computer vision
dc.subjectSensor networks
dc.subjectTracking accuracy
dc.subjectUnmanned ground vehicles
dc.subject.lcshMobile robots.
dc.subject.lcshComputer vision.
dc.titleReal-time detection performance of RTSP vs. USB cameras for UGVs
dc.typeJournal
oaire.citation.issue2025
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.affiliation.nameBRAC University
person.identifier.scopus-author-id60171552100
person.identifier.scopus-author-id60170877700
person.identifier.scopus-author-id60170431900
person.identifier.scopus-author-id60171772000
person.identifier.scopus-author-id60171328200
person.identifier.scopus-author-id60170432000
person.identifier.scopus-author-id60170198900
person.identifier.scopus-author-id57736022000

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