Monte Carlo simultaneous localization of multiple unknown transient radio sources using a mobile robot with a directional antenna

  • Authors:

  • Dezhen Song;Chang-Young Kim;Jingang Yi

  • Affiliations:

  • CS Department, Texas A&M University, College Station, TX;CS Department, Texas A&M University, College Station, TX;MAE Department, Rutgers University, Piscataway, NJ

  • Venue:
  • ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
  • Year:
  • 2009

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Abstract

We report our system and algorithm developments that enable a single mobile robot equipped with a directional antenna to simultaneously localize multiple unknown transient radio sources. Due to signal source anonymity, short transmission durations, and dynamic transmission patterns, the robot cannot treat the radio sources as continuous radio beacons. We model the radio source behaviors using a novel spatiotemporal probability occupancy grid (SPOG) that captures transient characteristics of radio transmissions and tracks the spatiotemporal posterior probability distribution of the radio transmissions. As a Monte Carlo method, we propose a ridge walking motion planning algorithm that enables the robot to efficiently traverse the high probability regions to accelerate the convergence of the posterior probability distribution. We have implemented the algorithms and the experiment results show that our method consistently outperforms methods such as a random walk or a fixed-route patrol mechanism.