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Active Magnetic Anomaly Detection Using Multiple Micro Aerial Vehicles

P. Dames,M. Schwager,D. Rus,Vijay R. Kumar

Published 2015 in IEEE Robotics and Automation Letters

ABSTRACT

Magnetic anomaly detection (MAD) is an important problem in applications ranging from geological surveillance to military reconnaissance. MAD sensors detect local disturbances in the magnetic field, which can be used to detect the existence of and to estimate the position of buried, hidden, or submerged objects, such as ore deposits or mines. These sensors may experience false positive and false negative detections and, without prior knowledge of the targets, can only determine proximity to a target. The uncertainty in the sensors, coupled with a lack of knowledge of even the existence of targets, makes the estimation and control problems challenging. We utilize a hierarchical decomposition of the environment, coupled with an estimation algorithm based on random finite sets, to determine the number of and the locations of targets in the environment. The small team of robots follow the gradient of mutual information between the estimated set of targets and the future measurements, locally maximizing the rate of information gain. We present experimental results of a team of quadrotor micro aerial vehicles discovering and localizing an unknown number of permanent magnets.

PUBLICATION RECORD

  • Publication year

    2015

  • Venue

    IEEE Robotics and Automation Letters

  • Publication date

    2015-12-01

  • Fields of study

    Geology, Computer Science, Engineering, Environmental Science

  • Identifiers
    DOI 10.1109/LRA.2015.2511444
  • External record

    Open on Semantic Scholar

  • Source metadata

    Semantic Scholar

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