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待翻譯:Mothership: A Two Tier Autonomous Refuse Collection System for Pedestrian Campuses

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AI 服務暫時不可用,以下為來源摘要,待恢復後補全翻譯:arXiv:2610.22461v1 Announce Type: new Abstract: Refuse collection in pedestrian campuses, parks and mixed-use districts remains manual because compaction trucks cannot reach bins located on walkways, courtyards and building service doors. This paper presents Mothership, a two-tier autonomous refuse collection system in which an electric compaction truck (the mothership) carries two low-speed sidewalk robots (RoboCarts) that fetch standard two-wheel bins, deliver them to the truck, return the empty bins to their original positions and re-dock on the truck for charging. The architecture separates responsibilities by scale: the truck performs road driving, compaction, lifting and energy supply, while the carts perform only sidewalk transport and bin grasping. This…

來源arXiv Robotics作者: Wei Wang (Robostreet research team. Cambridge, MA, USA), Yiru Veronika Wang (Robostreet research team. Cambridge, MA, USA), Yihan Wang (Robostreet research team. Cambridge, MA, USA), Zihao Li (Robostreet research team. Cambridge, MA, USA), Xiaohui Liang (Robostreet research team. Cambridge, MA, USA)
待翻譯:Mothership: A Two Tier Autonomous Refuse Collection System for Pedestrian Campuses
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[Submitted on 15 Oct 2026] Title:Mothership: A Two Tier Autonomous Refuse Collection System for Pedestrian Campuses View a PDF of the paper titled Mothership: A Two Tier Autonomous Refuse Collection System for Pedestrian Campuses, by Wei Wang and 6 other authors View PDF Abstract:Refuse collection in pedestrian campuses, parks and mixed-use districts remains manual because compaction trucks cannot reach bins located on walkways, courtyards and building service doors. This paper presents Mothership, a two-tier autonomous refuse collection system in which an electric compaction truck (the mothership) carries two low-speed sidewalk robots (RoboCarts) that fetch standard two-wheel bins, deliver them to the truck, return the empty bins to their original positions and re-dock on the truck for charging. The architecture separates responsibilities by scale: the truck performs road driving, compaction, lifting and energy supply, while the carts perform only sidewalk transport and bin grasping. This split removes the lift-and-tip mechanism from the sidewalk vehicle, keeping it light and low, and relaxes cart-to-truck docking tolerance to the +/-100 mm capture window of a standard automated lifter. We describe the system architecture, the bin-handling and docking interfaces, and a mission-planning formulation that decomposes a route into truck stop points and cart tasks. A discrete-event simulation over synthetic campus layouts with 2-16 bins/ha quantifies throughput as a function of bin density, cart count and stop-point radius. A two-cart configuration serves 20-29 bins/h. Throughput is governed by an interaction between cart count and stop-point radius: a single cart performs best with many close stops, whereas three or four carts need wide stops (80 m) to stay busy, reaching 35-49 bins/h at moderate-to-high densities. The best stop radius therefore has to be chosen together with the fleet size, not fixed in advance. Comments: 5 pages Subjects: Robotics (cs.RO) MSC classes: 14J60 (Primary) ACM classes: B.1.0 Report number: I-29 Cite as: arXiv:2610.22461 [cs.RO] (or arXiv:2610.22461v1 [cs.RO] for this version) https://doi.org/10.48550/arXiv.2610.22461 arXiv-issued DOI via DataCite (pending registration) Journal reference: Robots to the refuse, Jun. 10, 2016. https://researchmatters.psu.edu/2016/06/10/robots-to-the-refuse Submission history From: Wei Wang [view email] [v1] Thu, 15 Oct 2026 16:57:17 UTC (764 KB) Full-text links: Access Paper: View a PDF of the paper titled Mothership: A Two Tier Autonomous Refuse Collection System for Pedestrian Campuses, by Wei Wang and 6 other authors View PDF view license Additional Features Audio Summary Current browse context: cs.RO new | recent | 2026-10 Change to browse by: cs 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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