AI summary · arXiv: 2102.00702v1 · cs.RO
FEEL: Fast, Energy-Efficient Localization for Autonomous Indoor Vehicles
The essentials
- Autonomous vehicles have gained attention in both outdoor and indoor applications.
- Automation of processes within a warehouse using Autonomous Indoor Vehicles (AIV) is a notable indoor use-case.
- AIVs face the challenge of accurately locating themselves within centimeters and milliseconds while being energy-efficient.
- FEEL is an innovative indoor localization system that uses a fusion of three low-energy sensors: IMU, UWB, and radar.
- FEEL's software and hardware architecture are detailed in the paper.
- An Adaptive Sensing Algorithm (ASA) optimizes energy consumption by adjusting sensing frequency based on the environment's dynamics.
- ASA achieves up to 20% energy savings with minimal trade-offs in accuracy.
- Performance evaluation shows that FEEL offers exceptional localization accuracy with less than 7cm deviation from ground truth measurements.
- FEEL exhibits ultra-low latency of approximately 3ms.
- FEEL is an effective solution for meeting the stringent requirements of AIV localization.
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