An Analysis of Requirements for Rough Terrain Autonomous Mobility

The automatic generation of dense geometric models for autonomously navigating vehicles is a computationally expensive process. Using first principles, it is possible to quantify the relationship between the raw throughput required of the perception system and the maximum safely achievable speed of the vehicle. We show that terrain mapping perception is of polynomial complexity in the response distance. To the degree that geometric perception consumes time, it also degrades real-time response characteristics. Given this relationship, several strategies of adaptive geometric perception arise which are practical for autonomous vehicles.

[1]  Pascal Fua,et al.  Incremental Construction of Local D.E.M for an Autonomous Planetary Rover , 1993 .

[2]  Larry H. Matthies,et al.  Stochastic performance, modeling and evaluation of obstacle detectability with imaging range sensors , 1994, IEEE Trans. Robotics Autom..

[3]  Martial Hebert,et al.  Mapping and positioning for a prototype lunar rover , 1995, Proceedings of 1995 IEEE International Conference on Robotics and Automation.

[4]  John T. Bates PERCEPTION-REACTION TIME , 1995 .

[5]  M. G. Bekker,et al.  Off-the-road locomotion , 1960 .

[6]  Martial Hebert,et al.  Terrain Map Build-ing for Fast Navigation on Rough Terrain , 1992 .

[7]  Anthony Stentz Optimal and Efficient Path Planning for Unknown and Dynamic Environments , 1993 .

[8]  Takeo Kanade,et al.  3-D Vision Tech-niques for Autonomous Vehicles , 1988 .

[9]  Vladimir J. Lumelsky,et al.  The jogger's problem: accounting for body dynamics in real-time motion planning , 1995, Proceedings 1995 IEEE/RSJ International Conference on Intelligent Robots and Systems. Human Robot Interaction and Cooperative Robots.

[10]  M. Hebert,et al.  Hierarchical terrain representations for off-road navigation , 1991 .

[11]  Martial Hebert,et al.  3-D measurements from imaging laser radars: how good are they? , 1991, Proceedings IROS '91:IEEE/RSJ International Workshop on Intelligent Robots and Systems '91.

[12]  Larry H. Matthies,et al.  Perception control for obstacle detection by a cross-country rover , 1993, [1993] Proceedings IEEE International Conference on Robotics and Automation.

[13]  Martial Hebert,et al.  3D measurements from imaging laser radars: how good are they? , 1992, Image Vis. Comput..

[14]  A. Kelly,et al.  Obstacle detection for unmanned ground vehicles: a progress report , 1995, Proceedings of the Intelligent Vehicles '95. Symposium.

[15]  J. Dixon Linear and Non-Linear Steady State Vehicle Handling , 1988 .

[16]  D. Feng,et al.  Implementation of dynamic obstacle avoidance on the CMU NavLab , 1990, 1990 IEEE International Conference on Systems Engineering.

[17]  John G. Harris,et al.  Rigid body motion from range image sequences , 1991, CVGIP Image Underst..

[18]  I. Kweon Modeling rugged terrain by mobile robots with multiple sensors , 1991 .

[19]  B. Brown The Acceleration Due to Gravity , 1969 .

[20]  Uwe Franke,et al.  LONG DISTANCE DRIVING WITH THE DAIMLER-BENZ AUTONOMOUS VEHICLE VITA , 1991 .

[21]  David G. Morgenthaler,et al.  Obstacle Avoidance On Roadways Using Range Data , 1987, Other Conferences.

[22]  W. Shi,et al.  A partitioned control scheme for mobile robot path tracking , 1991, IEEE 1991 International Conference on Systems Engineering.

[23]  E. D. Dickmanns,et al.  A Curvature-based Scheme for Improving Road Vehicle Guidance by Computer Vision , 1987, Other Conferences.

[24]  M. G. Bekker,et al.  Theory of land locomotion , 1956 .

[25]  Benny M. Gothard,et al.  Stopping distance analysis of ladar and stereo for unmanned ground vehicles , 1995, Other Conferences.

[26]  Tsu-Shuan Chang,et al.  An Obstacle Avoidance Algorithm For An Autonomous Land Vehicle , 1987, Other Conferences.

[27]  Anthony Stentz,et al.  Dynamic trajectory planning for a cross-country navigator , 1993, Other Conferences.

[28]  John G. Harris,et al.  Autonomous cross-country navigation with the ALV , 1988, Proceedings. 1988 IEEE International Conference on Robotics and Automation.