Behavior-Based Mapping and Tracking with Multi-Robot Teams Using Probabilistic Techniques

Ashley Stroupe and Tucker Balch
Proceedings of the 2003 IEEE International Conference on Robotics and Automation (ICRA '03), May, 2003.


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Abstract
Abstract-We present a behavior-based approach for directing the movements of robot teams engaged in mapping and tracking target objects in their environment. The resulting paths optimize the vantage points for all the robots on the team ?therefore maximizing their information gain. At each step, each robot selects a direction for movement that will maximize the utility of its next observation. The global team behavior serves to optimize the team's knowledge because each robot considers the observational contributions of teammates. The utility of an observation is evaluated as the reduction of target uncertainty resulting from it. The approach is evaluated in simulation with static and moving targets. We evaluate performance by measuring the resulting expected uncertainty about target object locations compared to that of robots acting without regard to teammate locations and to that of global optimization over all robots for each single step. The qualitative behavior of the team is sensible and close to the single-step optimal set of trajectories.

Notes
Associated Lab(s) / Group(s): MultiRobot Lab
Number of pages: 8
Note: submitted

Text Reference
Ashley Stroupe and Tucker Balch, "Behavior-Based Mapping and Tracking with Multi-Robot Teams Using Probabilistic Techniques," Proceedings of the 2003 IEEE International Conference on Robotics and Automation (ICRA '03), May, 2003.

BibTeX Reference
@inproceedings{Stroupe_2003_4480,
   author = "Ashley Stroupe and Tucker Balch",
   title = "Behavior-Based Mapping and Tracking with Multi-Robot Teams Using Probabilistic Techniques",
   booktitle = "Proceedings of the 2003 IEEE International Conference on Robotics and Automation (ICRA '03)",
   month = "May",
   year = "2003",
   Notes = "submitted"
}