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Information Driven Coordinated Air-Ground Proactive Sensing
Lab Papers (GRASP)
  • Ben Grocholsky, University of Pennsylvania
  • Rahul Swaminathan, University of Pennsylvania
  • James Keller, University of Pennsylvania
  • Vijay Kumar, University of Pennsylvania
  • George J Pappas, University of Pennsylvania
Document Type
Conference Paper
Date of this Version
4-1-2005
Comments
Suggested Citation:
Grocholsky, B., R. Swaminathan, J. Keller, V. Kumar and G. Pappas. (2005). "Information Driven Coordinated Air-Ground Proactive Sensing." Proceedings of the 2005 IEEE International Conference on Robotics and Automation. Barcelona, Spain. April 2005.

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Abstract
This paper concerns the problem of actively searching for and localizing ground features by a coordinated team of air and ground robotic sensor platforms. The approach taken builds on well known Decentralized Data Fusion (DDF) methodology. In particular, it brings together established representations developed for identification and linearized estimation problems to jointly address feature detection and localization. This provides transparent and scalable integration of sensor information from air and ground platforms. As in previous studies, an Information theoretic utility measure and local control strategy drive the robots to uncertainty reducing team configurations. Complementary characteristics in terms of coverage and accuracy are revealed through analysis of the observation uncertainty for air and ground on-board cameras. Implementation results for a detection and localization example indicate the ability of this approach to scalably and effciently realize such collaborative potential.
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Citation Information
Ben Grocholsky, Rahul Swaminathan, James Keller, Vijay Kumar, et al.. "Information Driven Coordinated Air-Ground Proactive Sensing" (2005)
Available at: http://works.bepress.com/george_pappas/122/