Planning and Control in Unstructured Terrain

We consider the problem of autonomous navigation in an unstructured outdoor environment. We describe the planning and control aspects of an implemented system that drives a robot at modest speeds (∼1 m/s) over a variety of outdoor terrain. In real time, we use a gradient technique to plan globally optimal paths on a cost map, then employ a predictive dynamic controller to compute local velocity commands. Our planner and controller are considered the “best in class” among 10 teams competing in the DARPA Learning Applied to Ground Robotics (LAGR) program.

[1]  Hans P. Moravec,et al.  High resolution maps from wide angle sonar , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[2]  Anthony Stentz,et al.  Optimal and efficient path planning for partially-known environments , 1994, Proceedings of the 1994 IEEE International Conference on Robotics and Automation.

[3]  Alonzo Kelly.  A Feedforward Control Approach to the Local Navigation Problem for Autonomous Vehicles , 1994 .

[4]  Wolfram Burgard,et al.  The dynamic window approach to collision avoidance , 1997, IEEE Robotics Autom. Mag..

[5]  J A Sethian,et al.  Computing geodesic paths on manifolds. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Steven Dubowsky,et al.  Rapid physics-based rough-terrain rover planning with sensor and control uncertainty , 1999, Proceedings 1999 IEEE International Conference on Robotics and Automation (Cat. No.99CH36288C).

[7]  Kurt Konolige,et al.  A gradient method for realtime robot control , 2000, Proceedings. 2000 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2000) (Cat. No.00CH37113).

[8]  Roland Siegwart,et al.  An Interpolated Dynamic Navigation Function , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[9]  Robert C. Bolles,et al.  Outdoor Mapping and Navigation Using Stereo Vision , 2006, ISER.

[10]  Steven M. LaValle,et al.  Planning algorithms , 2006 .

[11]  Sebastian Thrun,et al.  Stanley: The robot that won the DARPA Grand Challenge , 2006, J. Field Robotics.

[12]  Pietro Perona,et al.  Learning to predict slip for ground robots , 2006, Proceedings 2006 IEEE International Conference on Robotics and Automation, 2006. ICRA 2006..

[13]  G. Swaminathan.  Robot Motion Planning , 2006 .

[14]  K. Konolige.  Rough Terrain Visual Odometry , 2007 .

[15]  Alonzo Kelly,et al.  State Space Sampling of Feasible Motions for High Performance Mobile Robot Navigation in Highly Constrained Environments , 2007, FSR.