Fast Scheduling of Multi-Robot Teams with Temporospatial Constraints
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RSS_2013_Final.pdf
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708.92 KB
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Adobe PDF
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Author(s)
Gombolay, Matthew C.
Wilcox, Ronald James
Shah, Julie A
Date Issued
June 2013
Journal
Robotics: Science and Systems IX
Publisher
Robotics: Science and Systems Foundation
Citation
Gombolay, Matthew, Ronald Wilcox, and Julie Shah. “Fast Scheduling of Multi-Robot Teams with Temporospatial Constraints.” Robotics: Science and Systems IX (June 23, 2013).
Version
Author's final manuscript
Abstract
New uses of robotics in traditionally manual manufacturing processes require the careful choreography of human and robotic agents to support safe and efficient coordinated work. Tasks must be allocated among agents and scheduled to meet temporal deadlines and spatial restrictions on agent proximity. These systems must also be capable of replanning onthe-fly to adapt to disturbances in the schedule and to respond to people working in close physical proximity. In this paper, we present a centralized algorithm, named Tercio, that handles tightly intercoupled temporal and spatial constraints and scales to larger problem sizes than prior art. Our key innovation is a fast, satisficing multi-agent task sequencer that is inspired by real-time processor scheduling techniques but is adapted to leverage hierarchical problem structure. We use this fast task sequencer in conjunction with a MILP solver, and show that we are able to generate near-optimal task assignments and schedules for up to 10 agents and 500 tasks in less than 20 seconds on average. Finally, we demonstrate the algorithm in a multi-robot hardware testbed.
MIT Department
Lincoln Laboratory
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Massachusetts Institute of Technology. Department of Mechanical Engineering
Terms of Use
Creative Commons Attribution-Noncommercial-Share Alike
Persistent DSpace Link
DOI of Published Version
http://dx.doi.org/10.15607/RSS.2013.IX.049
