AI Robotics

Autonomous navigation came a long way since our early work in 2004-2008 due to advances in computing, networking and sensors. However, the basic principles remains the same: environment, design, control, communications, power and intelligence.

Therefore, a drone navigating in a forest will differ from one in reconnaissance theater or a battle zone. Likewise, an auto driving car will differ from an underwater mobile robot. The field of AI robotics have significantly improved in situations where large data can be gathered to train ML algorithms; most notable on auto driving, where videos of driving patterns are available and rules of driving are set, and the road models are known. Our contribution has been in autonomous navigation, auto-refueling and 3D visualization. 

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A. Abdel-Hakim, Asem Ali, Chuck Sites, Amir Dizdarivic, Zlatco Sisic, Mike Miller and Aly Farag, “CVIP Lab Outdoor Navigation System” – TR  11-30-2004.​

M. S Hassouna, A. Abdel-Hakim and A. Farag “PDE-Based Robust Robotic Navigation,” Image, Vision and Computing, Vol.27, No. 1-2, pp. 10-18, January 2009.​

A Shalaby, A Ali, A Farag  “Simultaneous identification and tracking of moving targets”​ CVPR 2011 WORKSHOPS, 2011.