Abstract
In the field of navigation and guidance for mobile robots utilizing stereo visual imagery, the main problem to be solved is to detect the ground plane in acquired images by a stereo camera system mounted on the mobile device. This paper focuses on effective detection of ground based on graphical analysis of the gradient depth map evaluated on the input depth map within a given window. The detected ground planes is further divided into blocks and then classified into ground or non-ground regions for elimination of false detected ground planes followed by smoothing in refinement process. This proposed approach also has been shown to be effective in detection of obstacles appearing in the ground plane too while the mobile device is moving. In addition, the algorithm is simple, reliable, feasible, and may be efficiently exploited for implementation in an embedded hardware with limited resources for real-time applications.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Hast, A., Nysjö, J., Marchetti, A.: Optimal RANSAC – towards a repeatable algorithm for finding the optimal set. J. WSCG 21(1), 21–30 (2013)
Hu, X., Rodriguez, F.S.A., Gepperth, A.: A multi-modal system for road detection and segmentation. In: Intelligent Vehicles Symposium Proceedings. IEEE, pp. 1365–1370 (2014)
Sakai, A., Tamura, Y., Kuroda, Y.: Visual odometry using feature point and ground plane for urban environment. In: 2010 41st International Symposium on Robotics (ISR), and 2010 6th German Conference on Robotics (ROBOTIK), Munich, Germany, pp. 1–8 (2010)
Wang, Z., Zhao, J.: Optical flow based plane detection for mobile robot navigation. In: Proceedings of the 8th World Congress on Intelligent Control and Automation, Taipei, Taiwan, pp. 1156–1160 (2011)
Jamal, A., Mishra, P., Rakshit, S., Singh, A.K., Kumar, M.: Real-time ground plane segmentation and obstacle detection for mobile robot navigation. In: Emerging Trends in Robotics and Communication Technologies (INTERACT), pp. 314–317 (2010)
Gong, K., Green, R.: Ground-plane detection using stereo depth values for wheelchair guidance. In: 24th International Conference Image and Vision Computing New Zealand (IVCNZ), pp. 97–101 (2009)
Haberdar, H., Shah, S.K.: Disparity map refinement for video based scene change detection using a mobile stereo camera platform. In: 20th International Conference on Pattern Recognition (ICPR), pp. 3890–3893 (2010)
Teoh, C., Tan, C., Tan, Y.C.: Ground plane detection for autonomous vehicle in rainforest terrain. In: IEEE Conference on Sustainable Utilization and Development in Engineering and Technology (STUDENT), pp. 7–12 (2010)
Fayez, T.-K., Landes, T., Grussenmeyer, P.: Hough-transform and extended ransac algorithms for automatic detection of 3d building roof planes from lidar data. In: ISPRS Workshop on Laser Scanning 2007 and SilviLaser 2007, vol. 36, pp. 407–412 (2007)
Arro´spide, J., Salgado, L., Nieto, M., Mohedano, R.: Homography-based ground plane detection using a single on-board camera. IET Intell. Transp. Syst. 4(2), 149–160 (2010)
Mostof, N., Elhabiby, M., El-Sheimy, N.: Indoor localization and mapping using camera and inertial measurement unit (IMU). In: Position, Location and Navigation Symposium - PLANS 2014, 2014 IEEE/ION, pp. 1329–1335 (2014)
Mishra, P., Kishore, J.K., Shetty, R., Malhotra, A., Kukreja, R.: Department of electronics & communication engineering monocular vision based real-time exploration in autonomous rovers. In: 2013 International Conference on Advances in Computing, Communications and Informatics (ICACCI), pp. 42–46 (2013)
Yiningkarlli. http://blog.yiningkarlli.com/2010/11/city-street-playing-with-z-depth-and-ambient-occlusion.html
DeviantArt. http://mvramsey.deviantart.com/art/Vaulted-Cellar-depth-map-429569523
Evermotion. http://www.evermotion.org/tutorials/show/8320/tip-of-the-week-making-of-archmodels-vol-134-cover
The Foundry. http://community.thefoundry.co.uk/discussion/topic.aspx?f=36&t=48950
German Unix-AG Association. http://www.home.unix-ag.org/simon/files/street-canyon.html
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hoa, D.K., Cuong, P.T., Dzung, N.T. (2016). Gradient Depth Map Based Ground Plane Detection for Mobile Robot Applications. In: Nguyen, N.T., Trawiński, B., Fujita, H., Hong, TP. (eds) Intelligent Information and Database Systems. ACIIDS 2016. Lecture Notes in Computer Science(), vol 9621. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49381-6_69
Download citation
DOI: https://doi.org/10.1007/978-3-662-49381-6_69
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-662-49380-9
Online ISBN: 978-3-662-49381-6
eBook Packages: Computer ScienceComputer Science (R0)