Skip to main content
SpringerLink
Log in

Plane extraction for navigation of humanoid robot

  • Published:
Journal of Central South University Aims and scope Submit manuscript

Abstract

In order to make the humanoid robot walk freely in complicated circumstance, the reliable capabilities for obtaining plane information from its surroundings are demanded. A system for extracting planes from data taken by stereo vision was presented. After the depth image was obtained, the pixels of each line were scanned and split into straight line segments. The neighbouring relation of line segments was kept in link structure. The groups of three line segments were selected as seed regions. A queue was maintained for storing seed regions, and then the plane region was expanded around the seed region. The process of region growing continued until the queue of seed regions was empty. After trimming, the edges of the planes became smooth. In the end, extracted planes were obtained. In the experiment, two models were used: pipe and stairs. Two planes in pipe model and six planes in stairs model were extracted exactly. The speed and precision of algorithm can satisfy the demands of humanoid robot’s navigation.

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

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. GUTMANN J S, FUKUCHI M, FUJITA M. Stair climbing for humanoid robots using stereo vision [C]// Int Conf on Intelligent Robots and Systems (IROS). Sendai, Japan, 2004: 1407–1413.

  2. KANEHIRO F, HIRUKAWA H, KANEKO K, KAJITA S, FUJIWARA K, HARADA K, YOKOI K. Locomotion planning of humanoid robots to pass through narrow spaces [C]// Int Conf on Robotics and Automation (ICRA). New Orleans, 2004: 604–609.

  3. GUAN Y, YOKOI K, SIAN N E, TANIE K. Feasibility of humanoid robots stepping over obstacles [C]// Int Conf on Intelligent Robots and Systems (IROS). Sendai, Japan, 2004: 130–135.

  4. CHESTNUTT J, LAU M, CHEUNG G, KUFFNER J, HODGINS J, KANADE T. Footstep planning for the Honda ASIMO humanoid [C]// Proceedings of the IEEE International Conference on Robotics and Automation(ICRA’05). Piscataway, NJ, USA, 2005: 629–634.

  5. KUFFNER J J, KAGAMI S. Dynamically-stable motion planning for humanoid robots [J]. Autonomous Robots, 2002, 12(1): 105–118.

    Article  Google Scholar 

  6. ZONG Ying, SHI Wen, LI Xu. Optimal sagittal gait with ZMP stability during complete walking cycle for humanoid robots [J]. Journal of Control Theory and Applications, 2007, 5(2): 133–138.

    MATH  Google Scholar 

  7. ZOU Xiao-bing, CAI Zi-xing, SUN Guo-rung. Non-smooth environment modeling and global path planning for mobile robots [J]. Journal of Central South University of Technology, 2003, 10(3): 248–254.

    Article  Google Scholar 

  8. CHEN Xi, TAN Guan-zheng, JIANG Bin. Real-time optimal path planning for mobile robots based on immune genetic algorithm [J]. Journal of Central South University of Technology: Science and Technology, 2008, 39(3): 577–583. (in Chinese)

    Article  Google Scholar 

  9. GUTMANN J S, FUKUCHI M, FUJITA M. Real-time path planning for humanoid robot navigation [C]// Int Joint Conference on Artificial Intelligence. San Francisco, CA, USA, 2005: 1232–1237.

  10. ZHANG Tong, XIAO Nan-feng. Real-time map building for path planning of a humanoid robot [C]// Asia-Pacific Conference on Information Processing, 2009: 211–214.

  11. OKADA K, KAGAMI S, INABA M, INOUE H. Plane segment finder: Algorithm, implementation and applications [C]// Proceedings of the 2001 IEEE International Conference on Robotics & Automation. Seoul, Korea, 2001: 2120–2125.

  12. CHEN Ze-zhi, PEARS N E, LIANG Bo-jian, McDERMID J. Plane segmentation from two views in reciprocal-polar image space [C]// International Conference on Image Analysis and Recognition. Porto, Portugal, 2004: 638–646.

  13. LUD C, SU L, ZHU F, SHI Z. A general method for omnidirectional stereo camera calibration based on neural network optimizationl [J]. Lecture Notes in Computer Science, 2006, 3972: 383–389.

    Article  Google Scholar 

  14. BANKS J, CORKE P. Quantitative evaluation of matching methods and validity measures for stereo vision [J]. The International Journal of Robotics Research, 2001, 18(3): 512–532.

    Article  Google Scholar 

  15. KAGAMI S, TAKAOKA Y, KIDA Y, NISHIWAKI K, KANADE T. Online dense local 3D world reconstruction from stereo image sequences [C]// Proc of the IEEE/RSJ Int Conf on Intelligent Robots and Systems (IROS’05). Edmonton, Canada, 2005: 2999–3004.

Download references

Author information

Authors and Affiliations

  1. School of Computer Science and Engineering, South China University of Technology, Guangzhou, 510641, China

    Tong Zhang  (张彤) & Nan-Feng Xiao  (肖南峰)

  2. Computer Department, Guangdong Police Officers College, Guangzhou, 510230, China

    Tong Zhang  (张彤)

Authors
  1. Tong Zhang  (张彤)
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Nan-Feng Xiao  (肖南峰)
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Tong Zhang  (张彤).

Additional information

Foundation item: Project(60776816) supported by the National Natural Science Foundation of China and Civil Aviation Administration of China; Project (8251064101000005) supported by the Natural Science Foundation of Guangdong Province, China

Rights and permissions

Reprints and permissions

About this article

Cite this article

Zhang, T., Xiao, NF. Plane extraction for navigation of humanoid robot. J. Cent. South Univ. Technol. 18, 627–632 (2011). https://doi.org/10.1007/s11771-011-0740-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11771-011-0740-4

Key words

Search

Navigation