Limited range spatial load balancing in nonconvex environments using samplingbased motion planners
Abstract
This paper analyzes the limited range, spatial load balancing problem for agents deployed in nonconvex environments and subject to differential constraints which restricts how the agents can move. First, the (unlimited range) spatial load balancing problem is introduced and the minimization problem with area constraints is defined. Then, to extend the problem for limited ranges, two cost functions and a subpartition are defined. The problems are then analyzed and the results prove the existence of a partition that satisfies the area constraints. The nonconvex environment makes the problem difficult to solve in continuousspace. Therefore, a probabilistic roadmap is used to approximate agents’ cells via a graph. A distributed algorithm is proven to converge to an approximate solution. Lastly, the convergence of the algorithm is shown in simulation.
 Authors:

 Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
 Univ. of California, San Diego, La Jolla, CA (United States)
 Publication Date:
 Research Org.:
 Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
 Sponsoring Org.:
 USDOE
 OSTI Identifier:
 1459630
 Report Number(s):
 LAUR1627817
Journal ID: ISSN 09295593
 Grant/Contract Number:
 AC5206NA25396
 Resource Type:
 Accepted Manuscript
 Journal Name:
 Autonomous Robots
 Additional Journal Information:
 Journal Volume: 42; Journal Issue: 8; Journal ID: ISSN 09295593
 Publisher:
 Springer
 Country of Publication:
 United States
 Language:
 English
 Subject:
 42 ENGINEERING; Motion Planning; Coverage; Load Balancing; Robotics
Citation Formats
Boardman, Beth Leigh, Harden, Troy Anthony, and Martinez, Sonia. Limited range spatial load balancing in nonconvex environments using samplingbased motion planners. United States: N. p., 2018.
Web. doi:10.1007/s105140189713x.
Boardman, Beth Leigh, Harden, Troy Anthony, & Martinez, Sonia. Limited range spatial load balancing in nonconvex environments using samplingbased motion planners. United States. doi:10.1007/s105140189713x.
Boardman, Beth Leigh, Harden, Troy Anthony, and Martinez, Sonia. Mon .
"Limited range spatial load balancing in nonconvex environments using samplingbased motion planners". United States. doi:10.1007/s105140189713x. https://www.osti.gov/servlets/purl/1459630.
@article{osti_1459630,
title = {Limited range spatial load balancing in nonconvex environments using samplingbased motion planners},
author = {Boardman, Beth Leigh and Harden, Troy Anthony and Martinez, Sonia},
abstractNote = {This paper analyzes the limited range, spatial load balancing problem for agents deployed in nonconvex environments and subject to differential constraints which restricts how the agents can move. First, the (unlimited range) spatial load balancing problem is introduced and the minimization problem with area constraints is defined. Then, to extend the problem for limited ranges, two cost functions and a subpartition are defined. The problems are then analyzed and the results prove the existence of a partition that satisfies the area constraints. The nonconvex environment makes the problem difficult to solve in continuousspace. Therefore, a probabilistic roadmap is used to approximate agents’ cells via a graph. A distributed algorithm is proven to converge to an approximate solution. Lastly, the convergence of the algorithm is shown in simulation.},
doi = {10.1007/s105140189713x},
journal = {Autonomous Robots},
number = 8,
volume = 42,
place = {United States},
year = {2018},
month = {2}
}
Figures / Tables:
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Figures / Tables found in this record: