Skip to main content
SpringerLink
Log in

Improving the Generation of Rapidly Exploring Randomised Trees (RRTs) in Large Scale Virtual Environments Using Trails

  • Conference paper
Advances in Autonomous Robotics Systems (TAROS 2014)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 8717))

Included in the following conference series:

  • 3228 Accesses

Abstract

Rapidly exploring randomised trees (RRTs) are a useful tool generating maps for use by agents to navigate. A disadvantage to using RRTs is the length of time required to generate the map. In large scale environments, or those with narrow corridors, the time needed to create the map can be prohibitive. This paper explores a new method for improving the generation of RRTs in large scale environments. We look at using trails as a new source of information for the agent’s map building process. Trails are a set of observations of how other agents, human or AI, have navigated an environment. We evaluate RRT performance in two types of virtual environment, the first generated to cover a variety of scenarios an agent may face when building maps, the second is a set of ‘real’ virtual environments based in Second Life. By including trails we can improve the RRT generation step in most environments, allowing the RRT to be used to successfully plan routes using fewer points and reducing the length of the overall route.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Alempijevic, A., Fitch, R., Kirchner, N.: Bootstrapping navigation and path planning using human positional traces. In: 2013 IEEE International Conference on Robotics and Automation (ICRA), pp. 1242–1247. IEEE (2013)

    Google Scholar 

  2. Bradley, R.: The Prehistory of Britain and Ireland. Cambridge University Press (2007)

    Google Scholar 

  3. Branicky, M.S., LaValle, S.M., Olson, K., Yang, L.: Deterministic vs. probabilistic roadmaps. Submitted to the IEEE Transactions on Robotics and Automation (2002)

    Google Scholar 

  4. Branicky, M.S., LaValle, S.M., Olson, K., Yang, L.: Quasi-randomized path planning. In: IEEE International Conference on Robotics and Automation, ICRA 2001, vol. 2, pp. 1481–1487 (2001)

    Google Scholar 

  5. Chittaro, L., Ranon, R., Ieronutti, L.: Vu-flow: A visualization tool for analyzing navigation in virtual environments. IEEE Transactions on Visualization and Computer Graphics 12(6), 1475–1485 (2006)

    Article  Google Scholar 

  6. Geraerts, R., Overmars, M.H.: A comparative study of probabilistic roadmap planners. In: Workshop on the Algorithmic Foundations of Robotics (2002)

    Google Scholar 

  7. Grammenos, D., Filou, M., Papadakos, P., Stephanidis, C.: Virtual prints: leaving trails in virtual environments. In: Proceedings of the Workshop on Virtual Environments 2002, p. 131. Eurographics Association (2002)

    Google Scholar 

  8. Grammenos, D., Mourouzis, A., Stephanidis, C.: Virtual prints: Augmenting virtual environments with interactive personal marks. International Journal of Human-Computer Studies 64(3), 221–239 (2006)

    Article  Google Scholar 

  9. Jiang, J.-R., Huang, C.-C., Tsai, C.-H.: Avatar path clustering in networked virtual environments. In: ICPADS, pp. 845–850. IEEE (2010)

    Google Scholar 

  10. Kavraki, L.E., Svestka, P., Latombe, J.-C., Overmars, M.H.: Probabilistic roadmaps for path planning in high-dimensional configuration spaces. IEEE Transactions on Robotics and Automation 12(4), 566–580 (1996)

    Article  Google Scholar 

  11. Kuffner Jr, J.J., LaValle, S.M.: Rrt-connect: An efficient approach to single-query path planning. In: Proceedings of the IEEE International Conference on Robotics and Automation, ICRA 2000, vol. 2, pp. 995–1001. IEEE (2000)

    Google Scholar 

  12. Kumar, S., Chakravorty, S.: Adaptive sampling for generalized probabilistic roadmaps. Journal of Control Theory and Applications 10(1), 1–10 (2012)

    Article  MathSciNet  Google Scholar 

  13. LaValle, S.M.: Rapidly-exploring random trees: A new tool for path planning, Technical report, Iowa State University (1998)

    Google Scholar 

  14. Linden Research Inc. Second life official site (2012), http://secondlife.com (last accessed January 8, 2014)

  15. Miller, J.L., Crowcroft, J.: Avatar movement in world of warcraft battlegrounds. In: Proceedings of the 8th Annual Workshop on Network and Systems Support for Games, p. 1. IEEE Press (2009)

    Google Scholar 

  16. Myhill, C.: Commercial success by looking for desire lines. In: Masoodian, M., Jones, S., Rogers, B. (eds.) APCHI 2004. LNCS, vol. 3101, pp. 293–304. Springer, Heidelberg (2004)

    Chapter  Google Scholar 

  17. Park, B., Choi, J., Chung, W.K.: Path reconstruction method for sampling based planners. In: 2010 IEEE Workshop on Advanced Robotics and its Social Impacts, ARSO, pp. 81–86. IEEE (2010)

    Google Scholar 

  18. Pouke, M.: Using gps data to control an agent in a realistic 3d environment. In: 2013 Seventh International Conference on Next Generation Mobile Apps, Services and Technologies (NGMAST), pp. 87–92. IEEE (2013)

    Google Scholar 

  19. Ruddle, R.: The effect of trails on first-time and subsequent navigation in a virtual environment. In: VR 2005: Proceedings of the 2005 IEEE Conference 2005 on Virtual Reality, pp. 115–122, 321. IEEE Computer Society (2005)

    Google Scholar 

  20. Russell, S.J., Norvig, P.: Artificial Intelligence: A Modern Approach. Pearson Education (2003)

    Google Scholar 

  21. Samperi, K., Hawes, N., Beale, R.: Improving map generation in large-scale environments for intelligent virtual agents. In: The AAMAS 2013 Workshop on Cognitive Agents for Virtual Environments. LNCS. Springer (May 2013)

    Google Scholar 

  22. Samperi, K., Beale, R., Hawes, N.: Please keep off the grass: individual norms in virtual worlds. In: Proceedings of the 26th Annual BCS Interaction Specialist Group Conference on People and Computers, BCS-HCI 2012, pp. 375–380. British Computer Society (September 2012)

    Google Scholar 

  23. Stoffel, E.-P., Schoder, K., Ohlbach, H.J.: Applying hierarchical graphs to pedestrian indoor navigation. In: GIS 2008: Proceedings of the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, pp. 1–4. ACM, New York (2008)

    Google Scholar 

  24. Yee, N., Bailenson, J.N., Urbanek, M., Chang, F., Merget, D.: The unbearable likeness of being digital: The persistence of nonverbal social norms in online virtual environments. Cyberpsychology & Behavior: The Impact of the Internet, Multimedia and Virtual Reality on Behavior and Society 10(1), 115–121 (2007)

    Article  Google Scholar 

  25. Yuan, F., Twardon, L., Hanheide, M.: Dynamic path planning adopting human navigation strategies for a domestic mobile robot’. In: Intelligent Robots and Systems, pp. 3275–3281. IEEE (2010)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Aston Lab for Intelligent Collectives Engineering (ALICE), Aston Institute for Systems Analytics, Aston University, Birmingham, UK

    Katrina Samperi

  2. Intelligent Robotics Lab, School of Computer Science, University of Birmingham, Birmingham, UK

    Nick Hawes

Authors
  1. Katrina Samperi
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nick Hawes
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. School of Computer Science, University of Birmingham, Edgbaston, B15 2TT, Birmingham, UK

    Michael Mistry  & Aleš Leonardis  & 

  2. Circuits and Systems Group, Department of Electrical and Electronic Engineering, Imperial College London, Room 913c, Exhibition Road, SW7 2BT, London, UK

    Mark Witkowski

  3. Faculty of Computing, Engineering and Mathematical Sciences, University of the West of England, Coldharbour Lane, BS16 1QY, Bristol, UK

    Chris Melhuish

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer International Publishing Switzerland

About this paper

Cite this paper

Samperi, K., Hawes, N. (2014). Improving the Generation of Rapidly Exploring Randomised Trees (RRTs) in Large Scale Virtual Environments Using Trails. In: Mistry, M., Leonardis, A., Witkowski, M., Melhuish, C. (eds) Advances in Autonomous Robotics Systems. TAROS 2014. Lecture Notes in Computer Science(), vol 8717. Springer, Cham. https://doi.org/10.1007/978-3-319-10401-0_21

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-10401-0_21

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10400-3

  • Online ISBN: 978-3-319-10401-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation