CUSP: CUSUM-Governed Survival Hazard Alarms at the Perception Onset for Off-Road Navigation
To address this problem, we introduce CUSP (CUSUM-governed Survival model of the Perception onset), a model-agnostic runtime hazard alarm that learns this moment from intervention-terminated logs.
ProofPaper ↗
Key points
- Off-road navigation exposes a robot to potentially hazardous terrain en route.
- Although learning-based navigation uses safety supervision to choose which path to drive, it provides no runtime alarm when the robot following that path is heading into danger.
- "Cusp" is a word for the point at which one state is about to turn into another, and the moment we target is exactly such a cusp: the point at which safe driving turns unsafe in a human's judgment.
- A visual hazard head is trained on the annotated onset with a discrete-time survival objective so that driving with and without an onset both supervise the head, and a CUSUM accumulates the predicted onset risk into alarms.
Sources (1)
- [1]CUSP: CUSUM-Governed Survival Hazard Alarms at the Perception Onset for Off-Road NavigationarXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 6, 07:29 AM
To address this problem, we introduce CUSP (CUSUM-governed Survival model of the Perception onset), a model-agnostic runtime hazard alarm that learns this moment from intervention-terminated logs.
Off-road navigation exposes a robot to potentially hazardous terrain en route.
Extractive summary: sentences quoted from the sources.