This paper introduces a confidence-gated framework for vision-based heading prediction in UAV-UGV cooperative systems. The proposed method uses bounding-box area and heading variation as reliability proxies to determine when to trust the predicted heading for control commands. During low-confidence periods, it compares a baseline freeze-HOLD policy with a bounded-blend fallback, demonstrating that this approach improves command issuance accuracy and smoothness compared to simply holding commands. AI
IMPACT This research could enhance the reliability of autonomous systems by improving how they handle uncertain perception data.
RANK_REASON The cluster contains an academic paper detailing a new method for UAV-UGV cooperative systems.
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- alphaXiv
- arXiv
- CatalyzeX
- DagsHub
- freeze-HOLD
- Gotit.pub
- Hugging Face
- Influence Flower
- ScienceCast
- unmanned aerial vehicle
- unmanned ground vehicle
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