Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Cover of the book

2018 | OriginalPaper | Chapter

An Integrated Approach to Autonomous Environment Modeling

Authors : Miroslav Kulich, Viktor Kozák, Libor Přeučil

Published in: Modelling and Simulation for Autonomous Systems

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

In this paper, we present an integrated solution to memory-efficient environment modeling by an autonomous mobile robot equipped with a laser range-finder.
Majority of nowadays approaches to autonomous environment modelling, called exploration, employs occupancy grids as environment representation where the working space is divided into small cells each storing information about the corresponding piece of the environment in the form of a probabilistic estimate of its state. In contrast, the presented approach uses a polygonal representation of the explored environment which consumes much less memory, enables fast planning and decision-making algorithms and it is thus reliable for large-scale environments.
Simultaneous localization and mapping (SLAM) has been integrated into the presented framework to correct odometry errors and to provide accurate position estimates. This involves also refinement of the already generated environment model in case of loop closure, i.e. when the robot detects that it revisited an already explored place.
The framework has been implemented in Robot Operating System (ROS) and tested with a real robot in various environments. The experiments show that the polygonal representation with SLAM integrated can be used in the real world as it is fast, memory efficient and accurate. Moreover, the refinement can be executed in real-time during the exploration process.

Dont have a licence yet? Then find out more about our products and how to get one now:

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!

inform now

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!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
next chapter Autonomous 3D Exploration of Large Areas: A Cooperative Frontier-Based Approach
Footnotes
1
In our implementation, we use the Clipper library [13], which is an open-source polygon clipping library based on Vatti clipping algorithm. The library performs the boolean clipping operations - intersection, union, difference, and XOR. Moreover, it performs polygon offsetting.
 
Literature
1.
Amigoni, F.: Experimental evaluation of some exploration strategies for mobile robots. In: ICRA, pp. 2818–2823 (2008)
2.
Burgard, W., Moors, M., Stachniss, C., Schneider, F.: Coordinated multi-robot exploration. IEEE Trans. Robot. 21(3), 376–378 (2005)CrossRef
3.
Dakulović, M., Ileš, Š., Petrović, I.: Exploration and mapping of unknown polygonal environments based on uncertain range data. Automatika J. Control Meas. Electron. Comput. Commun. 52(2), 118–131 (2011)
4.
Ekman, A., Torne, A., Stromberg, D.: Exploration of polygonal environments using range data. IEEE Trans. Syst. Man Cybern. Part B Cybern. 27(2), 250–255 (1997)CrossRef
5.
Franchi, A., Freda, L., Oriolo, G., Vendittelli, M.: The sensor-based random graph method for cooperative robot exploration. IEEE/ASME Trans. Mechatron. 14(2), 163–175 (2009)CrossRef
6.
Freda, L., Oriolo, G.: Frontier-based probabilistic strategies for sensor-based exploration. In: Proceedings of the 2005 IEEE International Conference on Robotics and Automation, ICRA 2005, pp. 3881–3887, April 2005
7.
González-Baños, H.H., Latombe, J.C.: Navigation strategies for exploring indoor environments. Int. J. Robot. Res. 21(10–11), 829–848 (2002)CrossRef
8.
9.
Grisetti, G., Tipaldi, G.D., Stachniss, C., Burgard, W., Nardi, D.: Fast and accurate slam with rao-blackwellized particle filters. Robot. Auton. Syst. 55(1), 30–38 (2007)CrossRef
10.
Hershberger, J., Snoeyink, J.: Speeding up the Douglas-Peucker line-simplification algorithm. Technical report, University of British Columbia, Vancouver, BC, Canada (1992)
11.
Holz, D., Basilico, N., Amigoni, F., Behnke, S.: Evaluating the efficiency of frontier-based exploration strategies. In: ISR/ROBOTIK, pp. 1–8 (2010)
12.
Jia, S., Shen, H., Li, X., Cui, W., Wang, K.: Autonomous robot exploration based on hybrid environment model. In: 2012 IEEE International Conference on Information and Automation, pp. 19–24, June 2012
13.
14.
15.
Kuipers, B., Byun, Y.T.: A robot exploration and mapping strategy based on a semantic hierarchy of spatial representations. Robot. Auton. Syst. 8(1–2), 47–63 (1991)CrossRef
16.
17.
Newman, P., Bosse, M., Leonard, J.: Autonomous feature-based exploration. In: IEEE International Conference on Robotics and Automation, ICRA 2003. Proceedings, vol. 1, pp. 1234–1240 (2003)
18.
Poncela, A., Pérez, E.J., Bandera, A., Urdiales, C., Hernández, F.S.: Efficient integration of metric and topological maps for directed exploration of unknown environments. Robot. Auton. Syst. 41(1), 21–39 (2002)CrossRef
19.
Quigley, M., Conley, K., Gerkey, B.P., Faust, J., Foote, T., Leibs, J., Wheeler, R., Ng, A.Y.: ROS: an open-source robot operating system. In: ICRA Workshop on Open Source Software (2009)
20.
Rezanejad, M., Samari, B., Rekleitis, I., Siddiqi, K., Dudek, G.: Robust environment mapping using flux skeletons. In: 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 5700–5705, September 2015
21.
Shen, S., Michael, N., Kumar, V.: Autonomous indoor 3D exploration with a micro-aerial vehicle. In: 2012 IEEE International Conference on Robotics and Automation (ICRA), pp. 9–15 (2012)
22.
Siadat, A., Kaske, A., Klausmann, S., Dufault, M., Husson, R.: An optimized segmentation method for a 2D laser-scanner applied to mobilerobot navigation. In: 3rd IFAC Symposium on Intelligent Components and Instruments for Control Applications, pp. 153–158. Annecy, France, 9–11 June 1997. citeseer.​nj.​nec.​com/​181614.​html
23.
Vatti, B.R.: A generic solution to polygon clipping. Commun. ACM 35, 56–63 (1992)CrossRef
24.
Wurm, K., Stachniss, C., Burgard, W.: Coordinated multi-robot exploration using a segmentation of the environment (2008)
25.
Yamauchi, B.: Frontier-based exploration using multiple robots. In: Proceedings of the Second International Conference on Autonomous Agents, pp. 47–53 (1998)
26.
Zhang, Q.: Autonomous Indoor Exploration and Mapping using Hybrid Metric/Topological Maps. Ph.D. thesis, McGill University Libraries (2015)
Metadata
Title
An Integrated Approach to Autonomous Environment Modeling
Authors
Miroslav Kulich
Viktor Kozák
Libor Přeučil
Copyright Year
2018
Book
Modelling and Simulation for Autonomous Systems

Print ISBN: 978-3-319-76071-1

Electronic ISBN: 978-3-319-76072-8

Copyright Year: 2018

DOI
https://doi.org/10.1007/978-3-319-76072-8_1

Premium Partner

    Image Credits