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BEGIN:VEVENT
DTSTAMP:20260730T152640Z
LOCATION:Exhibit Hall
DTSTART;TZID=America/Los_Angeles:20260728T172300
DTEND;TZID=America/Los_Angeles:20260728T172400
UID:dac_DAC 2026_sess306_WIP3266@linklings.com
SUMMARY:Late Breaking Results: Energy-Aware Scheduling of Open-Vocabulary 
 Detection on Low-Power Mobile Robots
DESCRIPTION:Abdul Basit, Nurik Serikbayev, and Muhammad Shafique (New York
  University Abu Dhabi (NYUAD))\n\nOpen-vocabulary object detection enables
  language-driven object search for mobile robots, but on embedded GPUs a f
 ixed 8 Hz detector can dominate the mission energy budget. We propose an\n
 energy-aware runtime that couples a tri-state scheduler (SLEEP/EXPLORE/TRA
 CK at 1.5/4/8 Hz) with dual-precision switching between INT8 and FP16 YOLO
 -World-S on a Jetson Orin Nano robot. A tegrastats-based logger provides m
 ission energy and a task-level energy-per-detection metric. Across 48 real
 -robot missions, the scheduler cuts mission energy by 7.5% relative to a f
 ixed 8 Hz FP16 baseline while using 33% fewer inferences, and achieves sim
 ilar success rate and time-to-detect.\n\nTrack: Student\n\n
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