SLAM蒸馏到边缘芯片：2mW功耗下实现1000fps姿态估计，空间感知再无门槛
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TL;DR - The article surveys progress toward ultra-low-power, high-rate edge SLAM through model distillation and specialized chips. No single system yet achieves the headline target of 2 mW and 1,000 FPS simultaneously.
- Distilled SLAM models reportedly reduce size by 47.62% and FLOPs by 35.52%, with some experiments also improving pose accuracy.
- Navion demonstrated 2 mW visual-inertial odometry, while STM32N6-based Gideon reached 111 FPS; these are separate systems and benchmarks.
- ASICs, microcontrollers, heterogeneous SoCs, and spatial-computing chips offer different tradeoffs among power, speed, flexibility, and mapping capability.
- Potential applications include micro-drones, smart glasses, household robots, and autonomous industrial inspection.
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SLAM蒸馏到边缘芯片：2mW功耗下实现1000fps姿态估计，空间感知再无门槛
Public signals
N/A
TL;DR - The article surveys progress toward ultra-low-power, high-rate edge SLAM through model distillation and specialized chips. No single system yet achieves the headline target of 2 mW and 1,000 FPS simultaneously.
- Distilled SLAM models reportedly reduce size by 47.62% and FLOPs by 35.52%, with some experiments also improving pose accuracy.
- Navion demonstrated 2 mW visual-inertial odometry, while STM32N6-based Gideon reached 111 FPS; these are separate systems and benchmarks.
- ASICs, microcontrollers, heterogeneous SoCs, and spatial-computing chips offer different tradeoffs among power, speed, flexibility, and mapping capability.
- Potential applications include micro-drones, smart glasses, household robots, and autonomous industrial inspection.