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待翻译:Seeing What the Vehicle Sees: Video-Augmented Virtual Reality for Physical Autonomous Vehicles

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AI 服务暂时不可用,以下为来源摘要,待恢复后补全翻译:arXiv:2609.13224v1 Announce Type: new Abstract: Autonomous vehicles are expected to improve road safety and efficiency, but passengers often remain uncertain about what the vehicle perceives and why it acts as it does. Virtual reality (VR) offers a safe and repeatable medium for presenting this information, yet most passenger-facing VR studies rely on fully simulated vehicles or pre-scripted scenarios, so the motion and perception shown to the user do not originate from a physically operating autonomous system. This paper presents a video-augmented VR framework that couples a physical ROS 2 autonomous robot vehicle to a Unity 6 application deployed on a Meta Quest 3S headset. The vehicle state and live onboard camera stream are transmitted over two independent…

来源arXiv Robotics作者: Md Tanjemul Islam, Mohammad Shafin, Md Rafiul Kabir
待翻译:Seeing What the Vehicle Sees: Video-Augmented Virtual Reality for Physical Autonomous Vehicles
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[Submitted on 31 Aug 2026] Title:Seeing What the Vehicle Sees: Video-Augmented Virtual Reality for Physical Autonomous Vehicles View a PDF of the paper titled Seeing What the Vehicle Sees: Video-Augmented Virtual Reality for Physical Autonomous Vehicles, by Md Tanjemul Islam and 1 other authors View PDF HTML (experimental) Abstract:Autonomous vehicles are expected to improve road safety and efficiency, but passengers often remain uncertain about what the vehicle perceives and why it acts as it does. Virtual reality (VR) offers a safe and repeatable medium for presenting this information, yet most passenger-facing VR studies rely on fully simulated vehicles or pre-scripted scenarios, so the motion and perception shown to the user do not originate from a physically operating autonomous system. This paper presents a video-augmented VR framework that couples a physical ROS 2 autonomous robot vehicle to a Unity 6 application deployed on a Meta Quest 3S headset. The vehicle state and live onboard camera stream are transmitted over two independent communication channels, allowing the virtual vehicle to mirror the physical robot's motion while the passenger simultaneously views the vehicle's first-person camera feed and its navigation decisions through an in-vehicle dashboard interface. We evaluate the framework over 20 repeated closed-loop navigation trials. The system achieves a mean state-update latency of 29.63 ms, a mean relative route-progress error of 2.28% between the physical and virtual vehicles, and video delivery at 10.006 frames per second with 0.25% frame loss. All monitored navigation decisions were correctly reflected in the VR interface with no missed or incorrect notifications. The results indicate that the framework can support temporally synchronized, semantically consistent, and accurate route-progress representation for immersive observation of physical autonomous-vehicle behavior. Subjects: Robotics (cs.RO); Systems and Control (eess.SY) Cite as: arXiv:2609.13224 [cs.RO] (or arXiv:2609.13224v1 [cs.RO] for this version) https://doi.org/10.48550/arXiv.2609.13224 arXiv-issued DOI via DataCite Submission history From: Md Rafiul Kabir [view email] [v1] Mon, 31 Aug 2026 16:30:42 UTC (7,372 KB) Full-text links: Access Paper: View a PDF of the paper titled Seeing What the Vehicle Sees: Video-Augmented Virtual Reality for Physical Autonomous Vehicles, by Md Tanjemul Islam and 1 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.RO new | recent | 2026-09 Change to browse by: cs cs.SY eess eess.SY References & Citations NASA ADS Google Scholar Semantic Scholar Loading... Data provided by: Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)

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  • arXiv:2609.13224v1 Announce Type: new Abstract: Autonomous vehicles are expected to improve road safety and efficiency, but passengers often remain uncertain about what the vehicl…

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