Using shorelines for autonomous air vehicle guidance

We suggest the use of extended landmarks, such as shorelines, creeks, tree lines, and railroads, as well as roads for autonomous navigation of an unmanned air vehicle (UAV). In particular, we recommend the use of shorelines, because of their common availability, their ease of detection, and their significance in terms of events happening along them. Monitoring coastlines and waterways from low flying UAVs has many applications for military and civilian use. We report the development of a vision system that has enabled a prototype UAV to follow shorelines autonomously (without requiring maps or GPS). Using a near-infrared sensor the vision system distinguishes water from land (irrespective of water's color) and issues commands to the autopilot to follow the coastline or the riverbank. One insight of this problem is that the control algorithm could be integrated deeply with the vision system. This has the benefit of delaying smoothing/regularization so that it could occur in the context of the control coordinate system rather than the image or ground coordinate system. The algorithm itself is simple, but it possibly points the way to future algorithms which could more closely couple image processing and control. Furthermore, the experience gained in this work may be of value in the development of vision systems for following other types of paths.

[1]  Sebastian Thrun,et al.  Adaptive Road Following using Self-Supervised Learning and Reverse Optical Flow , 2005, Robotics: Science and Systems.

[2]  H. Liu,et al.  Automated extraction of coastline from satellite imagery by integrating Canny edge detection and locally adaptive thresholding methods , 2004 .

[3]  W. R. Philipson,et al.  Manual versus digital Landsat analysis for delineating river flooding , 1981 .

[4]  Martial Hebert,et al.  Vision and navigation for the Carnegie-Mellon Navlab , 1988 .

[5]  Raja Sengupta,et al.  Vision-Based Following of Structures Using an Unmanned Aerial Vehicle (UAV) , 2006 .

[6]  Xiao Xiao,et al.  Vision-based road-following using a small autonomous aircraft , 2004, 2004 IEEE Aerospace Conference Proceedings (IEEE Cat. No.04TH8720).

[7]  Larry S. Davis,et al.  A flexible tool for prototyping ALV road following algorithms , 1990, IEEE Trans. Robotics Autom..

[8]  Gregory D. Hager,et al.  The confluence of vision and control, Block Island Workshop on Vision and Control, June 23-27, 1997, Block Island, Rhode Island, USA , 1998, Block Island Workshop on Vision and Control.

[9]  Matthew Turk,et al.  VITS-A Vision System for Autonomous Land Vehicle Navigation , 1988, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  Stefano Soatto,et al.  A lagrangian formulation of nonholonomic path following , 1997, Block Island Workshop on Vision and Control.

[11]  W. Grossman,et al.  Autonomous Searching and Tracking of a River using an UAV , 2007, 2007 American Control Conference.

[12]  R. Frezza.  Path following for air vehicles in coordinated flight , 1999, 1999 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (Cat. No.99TH8399).

[13]  Karl Kluge.  YARF: An Open-Ended Framework for Robot Road Following , 1993 .