Dynamic Vehicle Routing for Robotic Systems
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Frazzoli_Dynamic vehicle.pdf
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Author(s) • • • •
Bullo, Francesco
Pavone, M.
Smith, S. L.
Frazzoli, Emilio
Savla, Ketan D.
Date Issued
September 2011
Journal
Proceedings of the IEEE
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Citation
Bullo, F., E. Frazzoli, M. Pavone, K. Savla, and S. L. Smith. “Dynamic Vehicle Routing for Robotic Systems.” Proceedings of the IEEE 99, no. 9 (September 2011): 1482-1504.
Version
Author's final manuscript
Abstract
Recent years have witnessed great advancements in the science and technology of autonomy, robotics, and networking. This paper surveys recent concepts and algorithms for dynamic vehicle routing (DVR), that is, for the automatic planning of optimal multivehicle routes to perform tasks that are generated over time by an exogenous process. We consider a rich variety of scenarios relevant for robotic applications. We begin by reviewing the basic DVR problem: demands for service arrive at random locations at random times and a vehicle travels to provide on-site service while minimizing the expected wait time of the demands. Next, we treat different multivehicle scenarios based on different models for demands (e.g., demands with different priority levels and impatient demands), vehicles (e.g., motion constraints, communication, and sensing capabilities), and tasks. The performance criterion used in these scenarios is either the expected wait time of the demands or the fraction of demands serviced successfully. In each specific DVR scenario, we adopt a rigorous technical approach that relies upon methods from queueing theory, combinatorial optimization, and stochastic geometry. First, we establish fundamental limits on the achievable performance, including limits on stability and quality of service. Second, we design algorithms, and provide provable guarantees on their performance with respect to the fundamental limits.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Laboratory for Information and Decision Systems
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Creative Commons Attribution-Noncommercial-Share Alike 3.0
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DOI of Published Version
https://doi.org/10.1109/jproc.2011.2158181