FALCON: FPGA-Accelerated Latency-Certifiable Occupancy Networks for Camera-Based Autonomous Driving
A perception system that must brake for a pedestrian does not need a low average latency. It must deliver an answer before the deadline on every frame, the worst case included. Commodity edge accelerators optimize the mean through dynamic scheduling, OS jitter, thermal throttling, and contention, so their per-frame latency can be measured but not bounded. We build FALCON, a camera-based 3D occupancy front-end on the AMD Kria KR260, an embedded FPGA drawing 4.3 W idle and up to 6.6 W under inference, and make the latency guarantee layered and explicit: programmable-logic (PL) compute is cycle-bounded analytically; inference is a measured envelope over 100k-frame traces; and a watchdog enfo...
| Authors | Haohua Que, Mingkai Liu, Handong Yao |
|---|---|
| Primary category | cs.CV |
| Published | 15 October 2026 |
| Last updated at source | 15 October 2026 |
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