[2605.05945] MobileEgo Anywhere: Open Infrastructure for long horizon egocentric data on commodity hardware

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Computer Science > Computer Vision and Pattern Recognition

arXiv:2605.05945 (cs)

[Submitted on 7 May 2026 (v1), last revised 14 May 2026 (this version, v4)]

Title:MobileEgo Anywhere: Open Infrastructure for long horizon egocentric data on commodity hardware

Authors:Senthil Palanisamy, Abhishek Anand, Satpal Singh Rathor, Pratyush Patnaik, Shubhanshu Khatana<br>View a PDF of the paper titled MobileEgo Anywhere: Open Infrastructure for long horizon egocentric data on commodity hardware, by Senthil Palanisamy and 4 other authors

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Abstract:The recent advancement of Vision Language Action (VLA) models has driven a critical demand for large scale egocentric datasets. However, existing datasets are often limited by short episode durations, typically spanning only a few minutes, which fails to capture the long horizon temporal dependencies necessary for complex robotic task execution. To bridge this gap, we present MobileEgo Anywhere, a framework designed to facilitate the collection of robust, hour plus egocentric trajectories using commodity mobile hardware. We leverage the ubiquitous sensor suites of modern smartphones to provide high fidelity, long term camera pose tracking, effectively removing the high hardware barriers associated with traditional robotics data collection. Our contributions are three fold: (1) we release a novel dataset comprising 200 hours of diverse, long form egocentric data with persistent state tracking; (2) we open source a mobile application that enables any user to record egocentric data, and (3) we provide a comprehensive processing pipeline to convert raw mobile captures into standardized, training ready formats for Vision Language Action model and foundation model research. By democratizing the data collection process, this work enables the massive scale acquisition of long horizon data across varied global environments, accelerating the development of generalizable robotic policies.

Subjects:

Computer Vision and Pattern Recognition (cs.CV); Computation and Language (cs.CL)

Cite as:<br>arXiv:2605.05945 [cs.CV]

(or<br>arXiv:2605.05945v4 [cs.CV] for this version)

https://doi.org/10.48550/arXiv.2605.05945

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arXiv-issued DOI via DataCite

Submission history<br>From: Senthil Palanisamy [view email]<br>[v1]<br>Thu, 7 May 2026 09:55:20 UTC (1,900 KB)

[v2]<br>Tue, 12 May 2026 04:53:52 UTC (1,900 KB)

[v3]<br>Wed, 13 May 2026 08:11:03 UTC (6,835 KB)

[v4]<br>Thu, 14 May 2026 07:57:22 UTC (6,835 KB)

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