Natural landmark extraction in cluttered forested environments

In this paper, a new systematical method for extracting tree trunk landmarks from 3D point clouds of cluttered forested environments is proposed. This purely geometric method is established on scene understanding and automatic analysis of trees. The pipeline of our method includes three steps. First, the raw point clouds are segmented by utilizing the circular shape of trees, and segments are grouped into tree sections based on the principle of spatial proximity. Second, circles and axes are extracted from tree sections which are subject to loss of shape information. Third, by clustering and integrating the tree sections resulted from various space inconsistencies, straight tree trunk landmarks are finally formed for future localization. The experimental results from real forested environments are presented.

[1]  Clark F. Olson,et al.  Probabilistic self-localization for mobile robots , 2000, IEEE Trans. Robotics Autom..

[2]  Daniel C. Asmar,et al.  Tree Trunks as Landmarks for Outdoor Vision SLAM , 2006, 2006 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'06).

[3]  Martial Hebert,et al.  A new approach to 3-D terrain mapping , 1999, Proceedings 1999 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human and Environment Friendly Robots with High Intelligence and Emotional Quotients (Cat. No.99CH36289).

[4]  Joachim Hertzberg,et al.  High-speed laser localization for mobile robots , 2005, Robotics Auton. Syst..

[5]  Timothy S. Bailey,et al.  Mobile Robot Localisation and Mapping in Extensive Outdoor Environments , 2002 .

[6]  Martial Hebert,et al.  Natural terrain classification using three‐dimensional ladar data for ground robot mobility , 2006, J. Field Robotics.

[7]  Aarne Halme,et al.  3-D mapping of natural environments with trees by means of mobile perception , 2005, IEEE Transactions on Robotics.

[8]  Bernardo Wagner,et al.  Using 3D laser range data for SLAM in outdoor environments , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[9]  Dieter Fox,et al.  Laser and Vision Based Outdoor Object Mapping , 2008, Robotics: Science and Systems.

[10]  Joachim Hertzberg,et al.  Heuristic-Based Laser Scan Matching for Outdoor 6D SLAM , 2005, KI.

[11]  Favio R. Masson,et al.  Simultaneous localization and map building using natural features and absolute information , 2002, Robotics Auton. Syst..

[12]  Michel Devy,et al.  Object-based modelling and localization in natural environments , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.