Visual-Wi-Fi Navigation to Signal-Emitting Devices

Key points

• Indoor navigation to task-relevant targets remains difficult when the target is small, occluded, or visually indistinct.1
• We study visual-Wi-Fi navigation, where a robot reaches a signal-emitting device in an unmapped environment using onboard visual observations and Wi-Fi packets overheard from the device, without connecting to the device or modifying infrastructure.1
• Realizing this requires pose-dependent Wi-Fi observations during closed-loop policy learning and reliable spatial cues from bearing measurements corrupted by indoor multipath propagation on a moving robot.1
• On top of it, we build ViFiNav, a localization-aware navigation framework: an online source-localization algorithm exploits robot motion to disambiguate and robustly aggregate bearings from multiple viewpoints into a confidence-aware source estimate, and a learned policy fuses this evolving estimate with depth observations and learns to act on it as it is refined.1

Sources (1)

• [1]Visual-Wi-Fi Navigation to Signal-Emitting Devices
  arXiv (AI, ML, NLP, CV, robotics, multi-agent) · Oct 8, 09:28 PM

  We present WiFiSpaces, which extends the Habitat embodied simulator with online ray-traced Wi-Fi sensing, rendering Wi-Fi observations for a robot-mounted antenna array at continuous poses during policy rollouts.

  Indoor navigation to task-relevant targets remains difficult when the target is small, occluded, or visually indistinct.

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