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Abstract

This book investigates real-time decision-making strategies for domain search and object classification treated as tasks competing for the same limited sensory resources using Multiple Autonomous Vehicles (MAV) over large-scale domains. In this chapter, we provide an overview of the literature on MAVs and their applications in search and classifications. Section 1.1 introduces the motivation and objectives of this book. Section 1.2 reviews the related literature on MAV systems, domain search, object classification and tracking, and decision-making strategies. Section 1.3 summarizes the organization of this book. Section 1.4 lists the research contribution.

Keywords

Mobile Sensor Domain Search Partially Observable Markov Decision Process Unknown Object Probability Hypothesis Density 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag London Ltd. 2012

Authors and Affiliations

  1. 1.Department of Electrical EngineeringUniversity of Notre DameNotre DameUSA
  2. 2.Department of Mechanical EngineeringWorcester Polytechnic InstituteWorcesterUSA

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