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International Conference on Augmented Reality, Virtual Reality and Computer Graphics

AVR 2017: Augmented Reality, Virtual Reality, and Computer Graphics pp 176–184Cite as

RRT* GL Based Path Planning for Virtual Aerial Navigation

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 10324))

Abstract

In this paper, we describe a path planning system for virtual navigation based on a RRT combination of RRT* Goal and Limit. The propose system includes a point cloud obtained from the virtual workspace with a RGB-D sensor, an identification module for interest regions and obstacles of the environment, and a collision-free path planner based on Rapidly-exploring Random Trees (RRT) for a safe and optimal virtual navigation of UAVs in 3D spaces.

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References

  1. Aguilar, W.G., Angulo, C.: Estabilización de vídeo en micro vehículos aéreos y su aplicación en la detección de caras. In: IX Congreso de Ciencia y Tecnología ESPE, Sangolquí, Ecuador (2014)

    Google Scholar 

  2. Aguilar, W.G., Angulo, C.: Real-time model-based video stabilization for microaerial vehicles. Neural Process. Lett. 43(2), 459–477 (2016)

    Article  Google Scholar 

  3. Aguilar, W.G., Angulo, C.: Real-time video stabilization without phantom movements for micro aerial vehicles. EURASIP J. Image Video Process. 1, 1–13 (2014)

    Google Scholar 

  4. Aguilar, W.G., Angulo, C.: Robust video stabilization based on motion intention for low-cost micro aerial vehicles. In: 11th International Multi-Conference on Systems, Signals & Devices (SSD), Barcelona, Spain (2014)

    Google Scholar 

  5. Koren, Y.: Robotics for Engineers (1998)

    Google Scholar 

  6. Aguilar, W.G., Angulo, C., Costa, R., Molina, L.: Control autónomo de cuadricópteros para seguimiento de trayectorias. In: IX Congreso de Ciencia y Tecnología ESPE, Sangolquí, Ecuador (2014)

    Google Scholar 

  7. Vasishth, O., Gigras, Y.: Path planning problem. Int. J. Comput. Appl. 104(2) (2014)

    Google Scholar 

  8. Cabras, P., Rosell, J., Pérez, A., Aguilar, W.G., Rosell, A.: Haptic-based navigation for the virtual bronchoscopy. In: 18th IFAC World Congress, Milano, Italy (2011)

    Google Scholar 

  9. Henry, P., Krainin, P., Herbst, E., Ren, X., Fox, D.: RGB-D mapping: using depth cameras for dense 3D modeling of indoor environments. In: The 12th International Symposium on Experimental Robotics (ISER) (2010)

    Google Scholar 

  10. Thrun, S., Burgard, W., Fox, D.: A real-time algorithm for mobile robot mapping with applications to multi-robot and 3D mapping. In: IEEE International Conference on Robotics and Automation, San Francisco (2000)

    Google Scholar 

  11. Gutmann, J.-S., Fukuchi, M., Fujita, M.: 3D perception and environment map generation for humanoid robot navigation. Int. J. Robot. Res. 27 (2008)

    Google Scholar 

  12. Oliver, A., Kang, S., Wunsche, B., MacDonald, B.: Using the kinect as a navigation sensor for mobile robotics. In: Conference on Image and Vision Computing New Zealand (2012)

    Google Scholar 

  13. Benavidez, P., Jamshidi, M.: Mobile robot navigation and target tracking system. In: The 6th International Conference on System of Systems Engineering, Albuquerque (2011)

    Google Scholar 

  14. Rao, D., Le, Q., Phoka, T., Quigley, M., Sudsang, A., Ng, A.Y.: Grasping novel objects with depth segmentation. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Taipei (2010)

    Google Scholar 

  15. Ali Shah, S.A., Bennamoun, M., Boussaid, F.: A novel algorithm for efficient depth segmentation using low resolution (kinect) images. In: IEEE 10th Conference on Industrial Electronics and Applications (ICIEA), Auckland (2015)

    Google Scholar 

  16. Liu, J., Yang, J., Liu, H., Tian, X., Gao, M.: An improved ant colony algorithm for robot path planning. Soft. Comput. 21, 1–11 (2016)

    Google Scholar 

  17. Glasius, R., Komoda, A., Gielen, S.C.A.M.: Neural network dynamics for path planning and obstacle avoidance. Neural Netw. 8(1), 125–133 (2000)

    Article  MATH  Google Scholar 

  18. Xin, D., Hua-hua, C., Wei-kang, G.: Neural network and genetic algorithm based global path planning in a static environment. J. Zhejiang Univ. Sci. A 6(6), 549–554 (2005-2006)

    Google Scholar 

  19. Seraji, H., Howard, A.: Behavior-based robot navigation on challenging terrain: a fuzzy logic approach. IEEE Trans. Robot. Autom. 18(3), 308–321 (2002)

    Article  Google Scholar 

  20. Kuffner, J.J., LaValle, S.M.: RRT-connect: an efficient approach to single-query path planning. In: IEEE International Conference on Robotics and Automation, San Francisco (2000)

    Google Scholar 

  21. Devaurs, D., Siméon, T., Cortés, J.: Efficient sampling-based approaches to optimal path planning in complex cost spaces. In: Akin, H.L., Amato, N.M., Isler, V., Stappen, A.F. (eds.) Algorithmic Foundations of Robotics XI. STAR, vol. 107, pp. 143–159. Springer, Cham (2015). doi:10.1007/978-3-319-16595-0_9

    Google Scholar 

  22. Gammell, J.D., Srinivasa, S., Barfoot, T.: Informed RRT*: optimal sampling-based path planning focused via direct sampling of an admissible ellipsoidal heuristic. In: IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2014) (2014)

    Google Scholar 

  23. Hatledal, L.I.: Kinect v2 SDK 2.0 – Colored Point Clouds, 15 August 2015. http://laht.info/kinect-v2-colored-point-clouds/

  24. Fankhauser, P., Bloesch, M., Rodriguez, D., Kaestner, R., Hutter, M. Siegwart, R.: Kinect v2 for mobile robot navigation: evaluation and modeling. In: 2015 International Conference on Advanced Robotics (ICAR), Istanbul (2015)

    Google Scholar 

  25. Myronenko, A., Song, X.: Point set registration: coherent point drift. IEEE Trans. Pattern Anal. Mach. Intell. 32(12), 2262–2275 (2010)

    Article  Google Scholar 

  26. Karaman, S., Frazzoli, E.: Incremental sampling-based algorithms for optimal motion planning. Int. J. Robot. Res. (2010)

    Google Scholar 

  27. Lachat, E., Hélene, M., Tania, L., Pierre, G.: Assessment and calibration of a RGB-D camera (Kinect v2 Sensor) towards a potential use for close-range 3D modeling. Remote Sens. 7(10) (2015)

    Google Scholar 

  28. Pagliari, D., Pinto, L.: Calibration of kinect for xbox one and comparison between the two generations of microsoft sensors. Sensors 15(11) (2015)

    Google Scholar 

  29. Eggert, D.W., Lorusso, A., Fisher, R.B.: Estimating 3-D rigid body transformations: a comparison of four major algorithms. Mach. Vis. Appl. 9, 272–290 (1997)

    Article  Google Scholar 

  30. Sreedhar, K., Panlal, B.: Enhancement of images using morphological transformations. Int. J. Comput. Sci. Inf. Technol. (IJCSIT) 4(1) (2012)

    Google Scholar 

  31. Aguilar, W.G., Angulo, C.: Compensación y aprendizaje de efectos generados en la imagen durante el desplazamiento de un robot. In: X Simposio CEA de Ingeniería de Control, Barcelona, Spain (2012)

    Google Scholar 

  32. Aguilar, W.G., Angulo, C.: Compensación de los efectos generados en la imagen por el control de navegación del robot Aibo ERS 7. In: VII Congreso de Ciencia y Tecnología ESPE, Sangolquí, Ecuador (2012)

    Google Scholar 

  33. Navon, E., Miller, O., Averbuch, A.: Color image segmentation based on adaptive local thresholds. Image Vis. Comput. 23, 69–85 (2005)

    Article  Google Scholar 

  34. Aguilar, W.G., Angulo, C.: Estabilización robusta de vídeo basada en diferencia de nivel de gris. In: VIII Congreso de Ciencia y Tecnología ESPE, Sangolquí, Ecuador (2013)

    Google Scholar 

  35. Sahoo, P.K., Soltani, S., Wong, A.K.C.: A survey of thresholding techniques. Comput. Vis. Graph. Image Process. 41, 233–260 (1988)

    Article  Google Scholar 

  36. The MathWorks, Inc.: Pcregrigid Documentation (2015). http://www.mathworks.com/help/vision/ref/pcregrigid.html. Accessed 24 Feb 2016

  37. Corke, P.I.: Robotics, Vision & Control: Fundamental Algorithms in MATLAB. Springer, Heidelberg (2011)

    Book  MATH  Google Scholar 

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Acknowledgement

This work is part of the projects VisualNavDrone 2016-PIC-024 and MultiNavCar 2016-PIC-025, from the Universidad de las Fuerzas Armadas ESPE, directed by Dr. Wilbert G. Aguilar.

Author information

Authors and Affiliations

  1. Dep. Seguridad y Defensa, Universidad de las Fuerzas Armadas ESPE, Sangolquí, Ecuador

    Wilbert G. Aguilar & Hugo Ruiz

  2. CICTE Research Center, Universidad de las Fuerzas Armadas ESPE, Sangolquí, Ecuador

    Wilbert G. Aguilar & Stephanie Morales

  3. GREC Research Group, Universitat Politècnica de Catalunya, Barcelona, Spain

    Wilbert G. Aguilar

  4. PLM Research Center, Purdue University, Lafayette, IN, USA

    Hugo Ruiz

  5. Universitat de Barcelona, Barcelona, Spain

    Vanessa Abad

Authors
  1. Wilbert G. Aguilar
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  2. Stephanie Morales
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  3. Hugo Ruiz
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  4. Vanessa Abad
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Corresponding author

Correspondence to Wilbert G. Aguilar .

Editor information

Editors and Affiliations

  1. University of Salento, Lecce, Italy

    Lucio Tommaso De Paolis

  2. University of Paris-Sud, Orsay, France

    Patrick Bourdot

  3. University of Salento, Lecce, Italy

    Antonio Mongelli

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Aguilar, W.G., Morales, S., Ruiz, H., Abad, V. (2017). RRT* GL Based Path Planning for Virtual Aerial Navigation. In: De Paolis, L., Bourdot, P., Mongelli, A. (eds) Augmented Reality, Virtual Reality, and Computer Graphics. AVR 2017. Lecture Notes in Computer Science(), vol 10324. Springer, Cham. https://doi.org/10.1007/978-3-319-60922-5_13

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  • DOI: https://doi.org/10.1007/978-3-319-60922-5_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60921-8

  • Online ISBN: 978-3-319-60922-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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