Skip to main content

2018 | OriginalPaper | Buchkapitel

Adapting Edge Weights for Optimal Paths in a Navigation Graph

verfasst von : Clemens Mühlbacher, Stefan Gspandl, Micheal Reip, Gerald Steinbauer

Erschienen in: Advances in Service and Industrial Robotics

Verlag: Springer International Publishing

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config
loading …

Abstract

Robots often use a topological graph to perform their navigation. To perform this navigation efficiently the traversal time along the edges of the graph needs to be properly estimated.
In this paper, we show an approach which estimates the traversal time along edges using only the information of the traversal time from one vertex to any other vertex in the graph. The approach does not need any detailed information which edges were actually traversed. Instead, it is assumed that the robot moves the fastest path in the graph.
To address the problem of noise measurements the approach uses a probabilistic model to estimate the traversal time. This paper we show how the probabilistic model can be simplified to allow to solve the estimation problem efficiently.
Finally, we show an evaluation of the approach on different sets of generated graphs and traversals showing that the approach estimates the of the traversal times for the shortest path correctly.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

Fußnoten
1
For space reasons we omit the proof but the proof follows closely the derivation of the equation.
 
Literatur
2.
Zurück zum Zitat Choset HM (2005) Principles of robot motion: theory, algorithms, and implementation. MIT press, CambridgeMATH Choset HM (2005) Principles of robot motion: theory, algorithms, and implementation. MIT press, CambridgeMATH
3.
Zurück zum Zitat Fentanes JP, Lacerda B, Krajník T, Hawes N, Hanheide M (2015) Now or later? Predicting and maximising success of navigation actions from long-term experience. In: 2015 IEEE international conference on robotics and automation (ICRA), pp 1112–1117. IEEE Fentanes JP, Lacerda B, Krajník T, Hawes N, Hanheide M (2015) Now or later? Predicting and maximising success of navigation actions from long-term experience. In: 2015 IEEE international conference on robotics and automation (ICRA), pp 1112–1117. IEEE
4.
Zurück zum Zitat Haigh KZ, Veloso MM (1999) Learning situation-dependent costs: improving planning from probabilistic robot execution. Robot Auton Syst 29(2):145–174CrossRef Haigh KZ, Veloso MM (1999) Learning situation-dependent costs: improving planning from probabilistic robot execution. Robot Auton Syst 29(2):145–174CrossRef
5.
Zurück zum Zitat Imlauer S, Mühlbacher C, Steinbauer G, Reip M, Gspandl S (2016) Hierarchical planning with traffic zones for a team of industrial transport robots. In: ICAPS workshop on distributed and multi-agent planning (DMAP-2016), pp 57–64 Imlauer S, Mühlbacher C, Steinbauer G, Reip M, Gspandl S (2016) Hierarchical planning with traffic zones for a team of industrial transport robots. In: ICAPS workshop on distributed and multi-agent planning (DMAP-2016), pp 57–64
6.
Zurück zum Zitat Kleiner A, Sun D, Meyer-Delius D (2011) ARMO: adaptive road map optimization for large robot teams. In: IEEE/RSJ international conference on intelligent robots and systems (IROS), pp 3276–3282 Kleiner A, Sun D, Meyer-Delius D (2011) ARMO: adaptive road map optimization for large robot teams. In: IEEE/RSJ international conference on intelligent robots and systems (IROS), pp 3276–3282
7.
Zurück zum Zitat Kucner T, Saarinen J, Magnusson M, Lilienthal AJ (2013) Conditional transition maps: learning motion patterns in dynamic environments. In: 2013 IEEE/RSJ international conference on intelligent robots and systems, pp 1196–1201. IEEE Kucner T, Saarinen J, Magnusson M, Lilienthal AJ (2013) Conditional transition maps: learning motion patterns in dynamic environments. In: 2013 IEEE/RSJ international conference on intelligent robots and systems, pp 1196–1201. IEEE
8.
Zurück zum Zitat Kümmerle R, Ruhnke M, Steder B, Stachniss C, Burgard W (2015) Autonomous robot navigation in highly populated pedestrian zones. J Field Robot 32(4):565–589CrossRef Kümmerle R, Ruhnke M, Steder B, Stachniss C, Burgard W (2015) Autonomous robot navigation in highly populated pedestrian zones. J Field Robot 32(4):565–589CrossRef
9.
Zurück zum Zitat Takaba S, Morita T, Hada T, Usami T, Yamaguchi M (1991) Estimation and measurement of travel time by vehicle detectors and license plate readers. In: Vehicle navigation and information systems conference, vol 2, pp 257–267. IEEE Takaba S, Morita T, Hada T, Usami T, Yamaguchi M (1991) Estimation and measurement of travel time by vehicle detectors and license plate readers. In: Vehicle navigation and information systems conference, vol 2, pp 257–267. IEEE
10.
Zurück zum Zitat Thrun S, Burgard W, Fox D (2005) Probabilistic robotics. MIT press, CambridgeMATH Thrun S, Burgard W, Fox D (2005) Probabilistic robotics. MIT press, CambridgeMATH
Metadaten
Titel
Adapting Edge Weights for Optimal Paths in a Navigation Graph
verfasst von
Clemens Mühlbacher
Stefan Gspandl
Micheal Reip
Gerald Steinbauer
Copyright-Jahr
2018
DOI
https://doi.org/10.1007/978-3-319-61276-8_41

Neuer Inhalt