Information-rich Task Allocation and Motion Planning for Heterogeneous Sensor Platforms
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Luders11_Infotech2.pdf
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841.98 KB
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Checksum (MD5)
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Author(s)
Luders, Brandon Douglas
Levine, Daniel S
Ponda, Sameera S
How, Jonathan P
Date Issued
March 2011
Journal
Infotech@Aerospace 2011
Publisher
American Institute of Aeronautics and Astronautics (AIAA)
Citation
Luders, Brandon, et al. "Information-Rich Task Allocation and Motion Planning for Heterogeneous Sensor Platforms." INFOTECH@AEROSPACE 2011, 29-31 March, 2011, St. Louis, Missouri, American Institute of Aeronautics and Astronautics, 2011. © 2011 by John P. How
Version
Author's final manuscript
Abstract
This paper introduces a novel stratified planning algorithm for teams of heterogeneous mobile sensors that maximizes information collection while minimizing resource costs. The main contribution of this work is the scalable unification of effective algorithms for de- centralized informative motion planning and decentralized high-level task allocation. We present the Information-rich Rapidly-exploring Random Tree (IRRT) algorithm, which is amenable to very general and realistic mobile sensor constraint characterizations, as well as review the Consensus-Based Bundle Algorithm (CBBA), offering several enhancements to the existing algorithms to embed information collection at each phase of the planning process. The proposed framework is validated with simulation results for networks of mobile sensors performing multi-target localization missions.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.2514/6.2011-1588
