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27 October 2010 Distributed, collaborative human-robotic networks for outdoor experiments in search, identify and track
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Abstract
This paper presents an overview of a human-robotic system under development at Cornell which is capable of mapping an unknown environment, as well as discovering, tracking, and neutralizing several static and dynamic objects of interest. In addition, the robots can coordinate their individual tasks with one another without overly burdening a human operator. The testbed utilizes the Segway RMP platform, with lidar, vision, IMU and GPS sensors. The software draws from autonomous systems research, specifically in the areas of pose estimation, target detection and tracking, motion and behavioral planning, and human robot interaction. This paper also details experimental scenarios of mapping, tracking, and neutralization presented by way of pictures, data, and movies.
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Daniel Lee, Mark McClelland, Joseph Schneider, Tsung-Lin Yang, Dan Gallagher, John Wang, Danelle Shah, Nisar Ahmed, Pete Moran, Brandon Jones, Tung-Sing Leung, Aaron Nathan, Hadas Kress-Gazit, and Mark Campbell "Distributed, collaborative human-robotic networks for outdoor experiments in search, identify and track", Proc. SPIE 7833, Unmanned/Unattended Sensors and Sensor Networks VII, 78330E (27 October 2010); https://doi.org/10.1117/12.868572
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