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Advanced Vertical Flight Laboratory

AVFL

Texas A&M University College of Engineering

Vision-Based Autonomous Landing

Precision autonomous approach and landing using a novel vision and imitation learning method in GPS denied environment

The objective of the project is to develop a novel control methodology for autonomous approach and landing, which is inspired by the procedure that Navy pilots follow for landing on space-constrained ship decks by utilizing the “horizon bar” (a standardized visual reference). The idea is to utilize machine vision to track a portable standardized visual cue, which a soldier can easily carry and install anywhere, even on a moving vehicle or a ship (similar to the “horizon bar”). Then combine the relative position and heading information from the vision system with imitation-learning-based control algorithms to bring an experienced pilot’s skill and decision-making process to a complex maneuver such as landing on a small ship deck or a dense urban terrain. This method has been successfully implemented on a quad-rotor and demonstrated autonomous tracking and landing on a moving platform. 

A demonstration of this technology in action onboard an autonomously landing quadcopter 

Students: Bochan Lee, Vishnu Saj, Keerat Singh

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Contact

Director
Dr. Moble Benedict
CV (.pdf)

741C HR Bright Bldg
Texas A&M University
College Station, TX 77843

Ph: 979-458-2705
benedict@tamu.edu

 

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