Autonomous ground vehicle path tracking

Autonomous ground vehicle navigation requires the integration of many technologies such as path planning, position and orientation sensing, vehicle control, and obstacle avoidance. The work presented here focuses on the control of a nonholonomic ground vehicle as it tracks a given path. A new path tracking technique called ‘‘vector pursuit’’ is presented. This new technique is based on the theory of screws, which was developed by Sir Robert Ball in 1900. It generates a desired vehicle turning radius based on the vehicle’s current position and orientation relative to the position of a point ahead on the planned path and the desired orientation along the path at that point. The vector pursuit algorithm is compared to other geometrical approaches, and it is shown to be more robust, resulting in more accurate path tracking. © 2004 Wiley Periodicals, Inc. • • • • • • • • • • • • • • • • • • • • • • • • • • • • • • •

[1]  S.X. Yang,et al.  Tracking control of a nonholonomic mobile robot by integrating feedback and neural dynamics techniques , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[2]  John T. Wen,et al.  Mobile robot navigation using sensor fusion , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[3]  Ching-Heng Ku,et al.  Smooth vision-based autonomous land vehicle navigation in indoor environments by person following using sequential pattern recognition , 1999, J. Field Robotics.

[4]  Renato Zaccaria,et al.  /spl mu/NAV: a minimalist approach to navigation , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[5]  임하영,et al.  Research of the Unmanned Vehicle Control and Modeling for Lane Tracking , 2003 .

[6]  Aníbal Ollero,et al.  Stability analysis of mobile robot path tracking , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[7]  Howie Choset,et al.  Composition of local potential functions for global robot control and navigation , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).

[8]  J. D. Everett.  A Treatise on the Theory of Screws , 1901, Nature.

[9]  N. D. Tillett,et al.  Row-following accuracy of an autonomous vision-guided agricultural vehicle , 1997 .

[10]  Philippe Martinet,et al.  Adaptive control for car like vehicles guidance relying on RTK GPS: rejection of sliding effects in agricultural applications , 2003, 2003 IEEE International Conference on Robotics and Automation (Cat. No.03CH37422).

[11]  Carl D. Crane,et al.  Autonomous path-planning navigation system for site characterization , 1996, Defense, Security, and Sensing.

[12]  K. Murphy.  ANALYSIS OF ROBOTIC VEHICLE STEERING AND CONTROLLER DELAY , 1994 .

[13]  Vijay Kumar,et al.  Closed loop navigation for mobile agents in dynamic environments , 2003, Proceedings 2003 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2003) (Cat. No.03CH37453).