September led a 13-paper quarter in monocular UAV odometry, 6 of 13

Asked:“A list of research papers on monocular odometry for UAVs in published in the third quarter of 2026”

A live-web search surfaced 13 papers on monocular visual or visual-inertial odometry with substantive UAV content, first made public or formally published 2026-07-01 through 2026-09-30, drawn from 7 source hosts. This is a broad research list, not a claim of bibliographic exhaustiveness: the total universe of Q3 2026 papers in this niche is not known. Twelve of the 13 fuse the monocular camera with an IMU or other sensors; one is vision-only.

Each dot is one paper, placed by first public availability. Colour marks modality: visual-inertial / multi-sensor (12) vision-only monocular (1). Hover a dot for the paper.

The one vision-only entry benchmarks five monocular SLAM systems on high-altitude nadir DJI footage with no inertial aiding — arxiv.org

Only one paper in the list is a formal journal publication with a resolved DOI landing page — the GTSAM-based indoor-UAV VIO in Drones, corroborated by 5 pages — doi.org

The smallest platform in the set is a Crazyflie nanodrone: TinyCVIO reports 3.5–3.7 cm trajectory error fully onboard across nine flights — arxiv.org

arXiv is the most common selected host but supports fewer than half the rows (6 of 13); 6 entries rest on a single retrieved page and are flagged in the table — arxiv.org

All 13 papers

Date	Paper & venue	Authors	Modality	Pages	Source

Live-web research list, 13 rows retrieved in Q3 2026 scope (2026-07-01 to 2026-09-30) across 7 independent source hosts; one source URL per row. Dates mean first public availability or formal publication as supported by the retrieved records; several entries are repository preprints. "Pages" counts corroborating retrieved pages; entries with 1 page are marked low corroboration. Modality labels (visual-inertial vs vision-only) follow the retrieved modality text and are not inferred beyond it. Authors left blank where unresolved. Full modality and UAV-relevance text shortened in the table for space; hover dots for titles.

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