The Generation of Directional Velocity Grid Map for Traversability Analysis of Unmanned Ground Vehicle

One of the basic technology for implementing the autonomy of UGV(Unmanned Ground Vehicle) is a path planning algorithm using obstacle and raw terrain information which are gathered from perception sensors such as stereo camera and laser scanner. In this paper, we propose a generation method of DVGM(Directional Velocity Grid Map) which have traverse speed of UGV for the five heading directions except the rear one. The fuzzy system is designed to generate a resonable traveling speed for DVGM from current patch to the next one by using terrain slope, roughness and obstacle information extracted from raw world model data. A simulation is conducted with world model data sampled from real terrain so as to verify the performance of proposed fuzzy inference system.

[1]  Regis Hoffman,et al.  Terrain Roughness Measurement from Elevation Maps , 1990, Other Conferences.

[2]  Hoffman,et al.  Terrain Roughness Regis Measurement fiom Elevation Maps , 1989 .

[3]  Edward Tunstel,et al.  Safe navigation on hazardous terrain , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[4]  F. G. Pin,et al.  Trajectory generation for car-like robots , 1990 .

[5]  Homayoun Seraji,et al.  Multi-range traversability indices for terrain-based navigation , 2002, Proceedings 2002 IEEE International Conference on Robotics and Automation (Cat. No.02CH37292).

[6]  Ronald C. Arkin,et al.  Reactive Speed Control System Based on Terrain Roughness Detection , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[7]  Zhao Chunxia,et al.  A generic approach to rugged terrain analysis based on fuzzy inference , 2004, ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004..

[8]  Homayoun Seraji.  Traversability index: a new concept for planetary rovers , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[9]  Cang Ye,et al.  T-transformation: traversability analysis for navigation on rugged terrain , 2004, SPIE Defense + Commercial Sensing.

[10]  Naokazu Yokoya,et al.  Fractal-based analysis and interpolation of 3D natural surface shapes and their application to terrain modeling , 1989, Comput. Vis. Graph. Image Process..

[11]  Homayoun Seraji,et al.  A rule-based fuzzy traversability index for mobile robot navigation , 2001, Proceedings 2001 ICRA. IEEE International Conference on Robotics and Automation (Cat. No.01CH37164).

[12]  Martial Hebert,et al.  A behavior-based system for off-road navigation , 1994, IEEE Trans. Robotics Autom..

[13]  Alberto Elfes,et al.  Using occupancy grids for mobile robot perception and navigation , 1989, Computer.