# Preprint reports faster wireless perception for resource-limited drones

_Published Tuesday, September 29, 2026 at 2:11 PM EDT · AI, Robotics, Science · Latest · Tier 2 — Notable_

Researchers report that FreshLatent improved a drone-oriented vision and language system's perception when its intermediate data was sent over a noisy wireless link. The adapter trains a small encoder and decoder to handle transmission errors while leaving the larger model unchanged.

In tests at 0 dB under the tightest communication budget, it improved two perception measures by 20.79 and 20.87 points over compression trained on clean data. On a Jetson AGX Xavier running in 10-W mode, its encoder used 7.7-9.9x less time and 8.8-10.0x less energy than a heavier codec. The results are from evaluated conditions, not a field deployment.

## Sources

- [cs.LG updates on arXiv.org](https://arxiv.org/abs/2609.30629)

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Canonical: https://techandbusiness.org/newswire/F8GhaOHpLezkFZO9YXhvoc
Published: 2026-09-29T18:11:05.453Z
Story chronology: 2026-09-29T04:00:00.000Z
Retrieved: 2026-09-29T19:40:37.610Z
Publisher: Tech & Business (techandbusiness.org)