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  • In this paper, we propose a framework for solving variants of the multi-goal path planning problem with applications to autonomous data collection. Autonomous data collection requires optimizing the trajectory of a mobile vehicle to collect data from a number of stationary sensors in a known configuration. The proposed approach utilizes the self-organizing map (SOM) architecture to provide a unified solution to multi-goal path planning problems. Our approach applies to cases where the vehicle must move within a radius of a sensor to collect data and also where some sensors can be ignored due to a lower priority. We compare our proposed approach to state-of-the-art approximate solutions to variants of the Traveling Salesman Problem (TSP) for random deployments and in an underwater monitoring application domain. Our results demonstrate that the SOM approach outperforms combinatorial heuristic algorithms and also provides a unified approach for solving variants of the multi-goal path planning problem.
  • In this paper, we propose a framework for solving variants of the multi-goal path planning problem with applications to autonomous data collection. Autonomous data collection requires optimizing the trajectory of a mobile vehicle to collect data from a number of stationary sensors in a known configuration. The proposed approach utilizes the self-organizing map (SOM) architecture to provide a unified solution to multi-goal path planning problems. Our approach applies to cases where the vehicle must move within a radius of a sensor to collect data and also where some sensors can be ignored due to a lower priority. We compare our proposed approach to state-of-the-art approximate solutions to variants of the Traveling Salesman Problem (TSP) for random deployments and in an underwater monitoring application domain. Our results demonstrate that the SOM approach outperforms combinatorial heuristic algorithms and also provides a unified approach for solving variants of the multi-goal path planning problem. (en)
Title
  • Unifying multi-goal path planning for autonomous data collection
  • Unifying multi-goal path planning for autonomous data collection (en)
skos:prefLabel
  • Unifying multi-goal path planning for autonomous data collection
  • Unifying multi-goal path planning for autonomous data collection (en)
skos:notation
  • RIV/68407700:21230/14:00225362!RIV15-GA0-21230___
http://linked.open...avai/riv/aktivita
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  • P(GP13-18316P)
http://linked.open...vai/riv/dodaniDat
http://linked.open...aciTvurceVysledku
http://linked.open.../riv/druhVysledku
http://linked.open...iv/duvernostUdaju
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  • 51958
http://linked.open...ai/riv/idVysledku
  • RIV/68407700:21230/14:00225362
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  • Conformal mapping; Heuristic algorithms; Intelligent robots; Motion planning; Traveling salesman problem Approximate solution; Data collection; Mobile vehicle; Path planning problems; Random deployment; Underwater monitoring; Unified approach (en)
http://linked.open.../riv/klicoveSlovo
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  • [E3D796CC1098]
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  • Chicago
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  • Piscataway
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  • Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems
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  • Faigl, Jan
  • Hollinger, G. A.
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
issn
  • 2153-0858
number of pages
http://bibframe.org/vocab/doi
  • 10.1109/IROS.2014.6942967
http://purl.org/ne...btex#hasPublisher
  • IEEE
https://schema.org/isbn
  • 978-1-4799-6934-0
http://localhost/t...ganizacniJednotka
  • 21230
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