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Johnson, Eric N.

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Author: Bershadsky, Dmitry × Author: Magree, Daniel ×

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    Development of a 500 gram Vision-based Autonomous Quadrotor Vehicle Capable of Indoor Navigation
    (Georgia Institute of Technology, 2015-05) Haviland, Stephen ; Bershadsky, Dmitry ; Magree, Daniel ; Johnson, Eric N.
    This paper presents the work and related research done in preparation for the American Helicopter Society (AHS) Micro Aerial Vehicle (MAV) Student Challenge. The described MAV operates without human interaction in search of a ground target in an open indoor environment. The Georgia Tech Quadrotor-Mini (GTQ-Mini) weighs under 500 grams and was specifically sized to carry a high processing computer. The system platform also consists of a monocular camera, sonar, and an inertial measurement unit (IMU). All processing is done onboard the vehicle using a lightweight powerful computer. A vision navigation system generates vehicle state data and image feature estimates in a vision SLAM formation using a Bierman Thornton extended Kalman Filter (BTEKF). Simulation and flight tests have been performed to show and validate the systems performance.
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    Georgia Tech Team Entry for the 2013 AUVSI International Aerial Robotics Competition
    (Georgia Institute of Technology, 2013-08) Magree, Daniel ; Bershadsky, Dmitry ; Costes, Chris ; Haviland, Stephen ; Sanz, David ; Kim, Eric ; Valdez, Pierre ; Dyer, Timothy ; Johnson, Eric N.
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    Georgia Tech Team Entry for the 2012 AUVSI International Aerial Robotics Competition
    (Georgia Institute of Technology, 2012-08) Magree, Daniel ; Bershadsky, Dmitry ; Wang, Xo ; Valdez, Pierre ; Antico, Jason ; Coder, Ryan ; Dyer, Timothy ; George, Eohan ; Johnson, Eric N.
    This paper describes the details of a Quadrotor Unmanned Aerial Vehicle capable of exploring cluttered indoor areas without relying on any external navigational aids. A Simultaneous Localization and Mapping (SLAM) algorithm is used to fuse information from a laser range sensor, an inertial measurement unit, and an altitude sonar to provide relative position, velocity, and attitude information. A wall avoidance and guidance system is implemented to ensure that the vehicle explores maximum indoor area. A model reference adaptive control architecture is used to ensure stability and mitigation of uncertainties. Finally, an object detection system is implemented to identify target objects for retrieval.
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    Georgia Tech Team Entry for the 2011 AUVSI International Aerial Robotics Competition
    (Georgia Institute of Technology, 2011-08) Chowdhary, Girish ; Magree, Daniel ; Bershadsky, Dmitry ; Dyer, Timothy ; George, Eohan ; Hashimoto, Hiroyuki ; Kalghatgi, Roshan ; Johnson, Eric N.
    his paper describes the details of a Quadrotor Unmanned Aerial Vehicle capable of exploring cluttered indoor areas without relying on any external navigational aids. An elaborate Simultaneous Localization and Mapping (SLAM) algorithm is used to fuse information from a laser range sensor, an inertial measurement unit, and an altitude sonar to provide relative position, velocity, and attitude information. A wall-following guidance rule is implemented to ensure that the vehicle explores maximum indoor area in a reasonable amount of time. A model reference adaptive control architecture is used to ensure stability and mitigation of uncertainties. The vehicle is intended to be Georgia Tech Aerial Robotic Team's entry for the 2011 International Aerial Robotics Competition (IARC) Symposium on Indoor Flight Issues.