Tracking Targets Using Multiple Robots: The Effect of Environment Occlusion

  • Authors:

  • Boyoon Jung;Gaurav S. Sukhatme

  • Affiliations:

  • Robotic Embedded Systems Laboratory (RESL), Robotics Research Laboratory, Department of Computer Science, University of Southern California, Los Angeles, CA 90089-0781, USA. boyoon@robotic ...;Robotic Embedded Systems Laboratory (RESL), Robotics Research Laboratory, Department of Computer Science, University of Southern California, Los Angeles, CA 90089-0781, USA. gaurav@robotic ...

  • Venue:
  • Autonomous Robots
  • Year:
  • 2002

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Abstract

This paper addresses the problem of tracking multiple targets using a network of communicating robots and stationary sensors. We introduce a iRegion-based Approach which controls robot deployment at two levels. A icoarse deployment controller distributes robots across regions using a topological map which maintains urgency estimates for each region, and a itarget-following controller attempts to maximize the number of tracked targets within a region. A behavior-based system is presented implementing the iRegion-Based Approach, which is fully distributed and scalable. We compared the iRegion-based Approach to a ‘naive’ local-following strategy in three environments with varying degree of occlusion. The experimental results showed that the iRegion-based Approach performs better than the naive strategy when the environment has significant occlusion. Second, we performed experiments (the environment was held constant) in which two techniques for computing urgency estimates were compared. Last, different combinations of mobile sensors and stationary sensors were compared in a given environment.