Skip to main content
SpringerLink
Log in
Book cover

Mapping, Planning and Exploration with Pose SLAM pp 53–87Cite as

Path Planning in Belief Space with Pose SLAM

  • Chapter
  • First Online:

Part of the book series: Springer Tracts in Advanced Robotics ((STAR,volume 119))

Abstract

The probabilistic belief networks that result from standard feature-based simultaneous localization and map building methods cannot be directly used to plan trajectories.

This is a preview of subscription content, 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   99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   129.99
Price excludes VAT (USA)
  • Durable hardcover 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

Learn about institutional subscriptions

Notes

  1. 1.

    Code accessed from: https://github.com/RainerKuemmerle/g2o.

  2. 2.

    GTSAM Version 3.2.1 accessed from: https://collab.cc.gatech.edu/borg/gtsam.

  3. 3.

    Accessed from: https://svn.openslam.org/data/svn/g2o/trunk/data/2d/manhattan3500/.

References

  1. S. Prentice, N. Roy, The Belief Roadmap: efficient planning in belief space by factoring the covariance. Int. J. Robot. Res. 29(11–12), 1448–1465 (2009)

    Article  Google Scholar 

  2. R. He, S. Prentice, N. Roy, Planning in information space for a quadrotor helicopter in a GPS-denied environment, in Proceedings of IEEE International Conference Robotics Automation (Pasadena, May 2008), pp. 1814–1820

    Google Scholar 

  3. R.M. Eustice, H. Singh, J.J. Leonard, M.R. Walter, Visually mapping the RMS Titanic: conservative covariance estimates for SLAM information filters. Int. J. Robot. Res. 25(12), 1223–1242 (2006)

    Article  Google Scholar 

  4. S. Thrun, S. Thayer, W. Whittaker, C. Baker, W. Burgard, D. Ferguson, D. Hahnel, M. Montemerlo, A. Morris, Z. Omohundro, C. Reverte, Autonomous exploration and mapping of abandoned mines. Robot. Automat. Mag. 11(4), 79–91 (2004)

    Article  Google Scholar 

  5. R. Smith, M. Self, P. Cheeseman, A stochastic map for uncertain spatial relationships, in Proceedings of 4th International Symposium Robotics Research (Santa Clara, 1988), pp. 467–474

    Google Scholar 

  6. K. Konolige, Large-scale map-making, in Proceedings of 19th AAAI Conference on Artificial Intelligence (San Jose, California, Jul 2004), pp. 457–463

    Google Scholar 

  7. S. Thrun, M. Montemerlo, The graph SLAM algorithm with applications to large-scale mapping of urban structures. Int. J. Robot. Res. 25(5–6), 403–429 (2006)

    Article  Google Scholar 

  8. U. Frese, L. Schröder, Closing a million-landmarks loop, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots System (Beijing, Oct 2006), pp. 5032–5039

    Google Scholar 

  9. G. Sibley, C. Mei, I. Reid, P. Newman, Vast-scale outdoor navigation using adaptive relative bundle adjustment. Int. J. Robot. Res. 29(8), 958–980 (2010)

    Article  Google Scholar 

  10. P.M. Newman, J. Leonard, J. Neira, J.D. Tardós, Explore and return: experimental validation of real time concurrent mapping and localization, in Proceedings of IEEE International Conference on Robotics Automation (Washington, May 2002), pp. 1802–1809

    Google Scholar 

  11. J. Guivant, E. Nebot, J. Nieto, F. Masson, Navigation and mapping in large unstructured environments. Int. J. Robot. Res. 23(4–5), 449–472 (2004)

    Article  Google Scholar 

  12. S. Rezaei, J. Guivant, J. Nieto, E. Nebot. Simultaneous information and global motion analysis (“SIGMA”) for car-like robots, in Proceedings of IEEE International Conference Robotics Automation (New Orleans, Apr 2004), pp. 1939–1944

    Google Scholar 

  13. L. Kavraki, P. Svestkaand, J.C. Latombe, M. Overmars, Probabilistic roadmaps for path planning in high dimensional configuration spaces. IEEE Trans. Robot. 12(4), 566–580 (1996)

    Article  Google Scholar 

  14. S. LaValle, J. Kuffner, Randomized kinodynamic planning. Int. J. Robot. Res. 20(5), 378–400 (2001)

    Article  Google Scholar 

  15. N. Ratliff, M. Zucker, J.A. Bagnell, S. Srinivasa, CHOMP: Gradient optimization techniques for efficient motion planning, in Proceedings of IEEE International Conference on Robotics Automation (Kobe, May 2009), pp. 489–494

    Google Scholar 

  16. S. Karaman, E. Frazzoli, Sampling-based algorithms for optimal motion planning. Int. J. Robot. Res. 30(7), 846–894 (2011)

    Article  MATH  Google Scholar 

  17. P. Missiuro, N. Roy, Adapting probabilistic roadmaps to handle uncertain maps, in Proceedings of IEEE International Conference on Robotics Automation (Orlando, May 2006), pp. 1261–1267

    Google Scholar 

  18. R. Pepy, M. Kieffer, E. Walter, Reliable robust path planner, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (Nice, Sep 2008), pp. 1655–1660

    Google Scholar 

  19. R. Alterovitz, T. Simeon, K. Goldberg, The Stochastic motion roadmap: a sampling framework for planning with Markov motion uncertainty, Robotics Science and Systems, vol. 3 (Atlanta, 2007)

    Google Scholar 

  20. A. Bry, N. Roy, Rapidly-exploring Random Belief Trees for motion planning under uncertainty, in Proceedings of IEEE International Conference on Robotics Automation (Shanghai, May 2011), pp. 723–730

    Google Scholar 

  21. V. Ila, J.M. Porta, J. Andrade-Cetto, Information-based compact Pose SLAM. IEEE Trans. Robot. 26(1), 78–93 (2010)

    Article  Google Scholar 

  22. F. Lu, E. Milios, Globally consistent range scan alignment for environment mapping. Auton. Robot. 4(4), 333–349 (1997)

    Article  Google Scholar 

  23. R.M. Eustice, H. Singh, J.J. Leonard, Exactly sparse delayed-state filters for view-based SLAM. IEEE Trans. Robot. 22(6), 1100–1114 (2006)

    Article  Google Scholar 

  24. K. Konolige, M. Agrawal, FrameSLAM: from bundle adjustment to realtime visual mapping. IEEE Trans. Robot. 24(5), 1066–1077 (2008)

    Article  Google Scholar 

  25. N. Michael, E. Stump, K. Mohta. Persistent surveillance with a team of MAVs, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (San Francisco, Sep 2011), pp. 2708–2714

    Google Scholar 

  26. A. Zini, Robots expand delivery options. Health Management Technology (March 2011), pp. 10–12

    Google Scholar 

  27. R. Platt, R. Tedrake, L. Kaelbling, T. Lozano-Perez, Belief space planning assuming maximum likelihood observations, Robotics Science and Systems, vol. 6 (Zaragoza, Spain, 2010)

    Google Scholar 

  28. R. Valencia, J. Andrade-Cetto, J.M. Porta, Path planning in belief space with Pose SLAM, in Proceedings of IEEE International Conference on Robotics Automation (Shanghai, May 2011), pp. 78–83

    Google Scholar 

  29. L. Jaillet, J. Cortés, T. Siméon, Sampling-based path planning on configuration-space costmaps. IEEE Trans. Robot. 26(4), 635–645 (2010)

    Article  Google Scholar 

  30. R. Sim, N. Roy, Global A-optimal robot exploration in SLAM, in Proceedings of IEEE International Conference on Robotics Automation (Barcelona, Apr 2005), pp. 661–666

    Google Scholar 

  31. V. Ila, J.M. Porta, J. Andrade-Cetto, Amortized constant time state estimation in Pose SLAM and hierarchical SLAM using a mixed Kalman-information filter. Robot. Auton. Syst. 59(5), 310–318 (2011)

    Article  Google Scholar 

  32. Y. Chen, T.A. Davis, W.W. Hager, S. Rajamanickam, Algorithm 887: CHOLMOD, supernodal sparse Cholesky factorization and update/downdate. ACM T. Math. Softw. 35(3), 22:1–22:14 (2008)

    Google Scholar 

  33. S. Thrun, Y. Liu, D. Koller, A.Y. Ng, Z. Ghahramani, H. Durrant-Whyte, Simultaneous localization and mapping with sparse extended information filters. Int. J. Robot. Res. 23(7–8), 693–716 (2004)

    Article  Google Scholar 

  34. M. Quigley, B. Gerkey, K. Conley, T. Foote J. Faust, J. Leibs, E. Berger, R. Wheeler, A.Y. Ng, ROS: an open-source robot operating system, in Proceedings of IEEE ICRA Workshop Open Source Software Robotics (Kobe, 2009)

    Google Scholar 

  35. A. Howard, N. Roy, The robotics data set repository (Radish) (2003), http://radish.sourceforge.net

  36. E. Olson, J. Leonard, S. Teller, Fast iterative alignment of pose graphs with poor initial estimates, in Proceedings of IEEE International Conference on Robotics Automation (Orlando, May 2006), pp. 2262–2269

    Google Scholar 

  37. E.H. Teniente, J. Andrade-Cetto, FaMSA: fast multi-scan alignment with partially known correspondences, in Proceedings of European Conference on Mobile Robotics (Orebro, Sep 2011), pp. 139–144

    Google Scholar 

  38. S. Foix, G. Alenyà, J. Andrade-Cetto, C. Torras, Object modeling using a ToF camera under an uncertainty reduction approach, in Proceedings of IEEE International Conference on Robotics Automation (Anchorage, May 2010), pp. 1306–1312

    Google Scholar 

  39. D. Fox, W. Burgard, S. Thrun, The dynamic window approach to collision avoidance. Robot. Autom. Mag. 4(1), 23–33 (1997)

    Article  Google Scholar 

  40. R. Kummerle, G. Grisetti, H. Strasdat, K. Konolige, W. Burgard, g2o:a general framework for graph optimization, in Proceedings of IEEE International Conference on Robotics Automation (Shanghai, May 2011), pp. 3607–3613

    Google Scholar 

  41. F. Dellaert, M. Kaess, Square root SAM: simultaneous localization and mapping via square root information smoothing. Int. J. Robot. Res. 25(12), 1181–1204 (2006)

    Article  MATH  Google Scholar 

  42. M. Kaess, A. Ranganathan, F. Dellaert, iSAM: Incremental smoothing and mapping. IEEE Trans. Robot. 24(6), 1365–1378 (2008)

    Article  Google Scholar 

  43. M. Kaess, H. Johannsson, R. Roberts, V. Ila, J. Leonard, F. Dellaert, iSAM2: Incremental smoothing and mapping using the bayes tree. Int. J. Robot. Res. 31(2), 216–235 (2012)

    Article  Google Scholar 

  44. S. Thrun, Monte Carlo POMDPs, in Advances in Neural Information Processing Systems 12 (The MIT Press, Apr 1999), pp. 1064–1070

    Google Scholar 

  45. J.M. Porta, N. Vlassis, M.T.J. Spaan, P. Poupart, Point-based value iteration for continuous POMDPs. J. Mach. Learn. Res. 7, 2329–2367 (2006)

    MathSciNet  MATH  Google Scholar 

  46. E.J. Sondik, The optimal control of partially observable Markov processes over the infinite horizon: discounted cost. Oper. Res. 26, 282–304 (1978)

    Article  MathSciNet  MATH  Google Scholar 

  47. L.P. Kaelbling, M.L. Littman, A.R. Cassandra, Planning and acting in partially observable stochastic domains. Artif. Intell. 101, 99–134 (1995)

    Article  MathSciNet  MATH  Google Scholar 

  48. J. Pineau, G. Gordon, S. Thrun, Point-based value iteration: an anytime algorithm for POMDPs, in Proceedings of International Joint Conference Artificial Intelligent (Acapulco, 2003)

    Google Scholar 

  49. M.T.J. Spaan, N.A. Vlassis, Perseus: randomized point-based value iteration for POMDPs. J. Artif. Intell. Res. 24, 195–220 (2005)

    MATH  Google Scholar 

  50. J.-C. Latombe, Robot Motion Planning (Kluwer Academic, London, 1991)

    Book  MATH  Google Scholar 

  51. J.F. Canny, The Complexity of Robot Motion Planning (MIT Press, 1988)

    Google Scholar 

  52. S. Ross, B. Chaib-Draa, J. Pineau, Bayesian reinforcement learning in continuous POMDPs with application to robot navigation, in Proceedings of IEEE International Conference on Robotics Automation (Pasadena, May 2008), pp. 2845–2851

    Google Scholar 

  53. P. Dallaire, C. Besse, S. Ross, B. Chaib-draa, Bayessian reinforcement learning in continuous POMDPs with Gaussian processes, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (Saint Louis, Oct 2009), pp. 2604–2609

    Google Scholar 

  54. N. Roy, S. Thrun, Coastal navigation with mobile robots, in Advances in Neural Information Processing Systems 12 (The MIT Press, Apr 1999), pp. 1043–1049

    Google Scholar 

  55. J.P. Gonzalez, A. Stentz, Planning with uncertainty in position using high-resolution maps, in Proceedings of IEEE International Conference on Robotics Automation (Rome, Apr 2007), pp. 1015–1022

    Google Scholar 

  56. J. Lee, C. Pippin, T. Balch, Cost based planning with RRT in outdoor environments, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (Nice, Sep 2008), pp. 684–689

    Google Scholar 

  57. L. Jaillet, J. Cortés, T. Siméon, Transition-based RRT for path planning in continuous cost spaces, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (Nice, Sep 2008), pp. 2145–2150

    Google Scholar 

  58. R. Kummerle, D. Hahnel, D. Dolgov, S. Thrun, W. Burgard, Autonomous driving in a multi-level parking structure, in Proceedings of IEEE International Conference on Robotics Automation (Kobe, May 2009), pp. 3395–3400

    Google Scholar 

  59. D. Dolgov, S. Thrun, Autonomous driving in semi-structured environments: mapping and planning, in Proceedings of IEEE International Conference on Robotics Automation (Kobe, May 2009), pp. 3407–3414

    Google Scholar 

  60. H. Choset, K. Nagatani, Topological simultaneous localization and mapping (SLAM): toward exact localization without explicit localization. IEEE Trans. Robot. Autom. 17(2), 125–137 (2001)

    Article  Google Scholar 

  61. F. Fraundorfer, C. Engels, D. Nister, Topological mapping, localization and navigation using image collections, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (San Diego, Nov 2007), pp. 3872–3877

    Google Scholar 

  62. T. Goedeme, M. Nuttin, T. Tuytelaars, L. Van Gool, Omnidirectional vision based topological navigation. Int. J. Comput. Vision 74(3), 219–236 (2007)

    Article  Google Scholar 

  63. S. Thrun, Learning metric-topological maps for indoor mobile robot navigation. Artif. Intell. 99(1), 21–71 (1998)

    Article  MATH  Google Scholar 

  64. M.A. Whitty, J. Guivant, Efficient path planning in deformable maps, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (Saint Louis, Oct 2009), pp. 5401–5406

    Google Scholar 

  65. M.A. Whitty, J. Guivant, Efficient global path planning during dense map deformation, in Proceedings of IEEE International Conference on Robotics Automation (Shanghai, May 2011), pp. 4943–4949

    Google Scholar 

  66. K. Konolige, E. Marder-Eppstein, B. Marthi, Navigation in hybrid metric-topological maps, in Proceedings of IEEE International Conference on Robotics Automation (Shanghai, May 2011), pp. 3041–3047

    Google Scholar 

  67. T. Kollar, N. Roy, Efficient optimization of information-theoretic exploration in SLAM, in Proceedings of 23th AAAI Conference on Artificial Intelligence (Chicago, Jul 2008), pp. 1369–1375

    Google Scholar 

  68. R. Valencia, J. Valls Miró, G. Dissanayake, J. Andrade-Cetto, Active pose SLAM, in Proceedings of IEEE/RSJ International Conference on Intelligent Robots and Systems (Algarve, Oct 2012), pp. 1885–1891

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Carnegie Mellon University, Pittsburgh, PA, USA

    Rafael Valencia

  2. CSIC-UPC, Institut de Robòtica i Informàtica Industrial, Barcelona, Spain

    Juan Andrade-Cetto

Authors
  1. Rafael Valencia
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Juan Andrade-Cetto
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rafael Valencia .

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG

About this chapter

Cite this chapter

Valencia, R., Andrade-Cetto, J. (2018). Path Planning in Belief Space with Pose SLAM. In: Mapping, Planning and Exploration with Pose SLAM. Springer Tracts in Advanced Robotics, vol 119. Springer, Cham. https://doi.org/10.1007/978-3-319-60603-3_4

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-60603-3_4

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60602-6

  • Online ISBN: 978-3-319-60603-3

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation