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Johnson, Eric N.

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Author: Chowdhary, Girish × Author: Sobers, D. Michael Jr. ×

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Design, Development, and Testing of a Low Cost, Fully Autonomous Indoor Unmanned Aerial System

2010-08 , Chowdhary, Girish , Sobers, D. Michael Jr. , Salaün, Erwan , Ottander, John , Johnson, Eric N.

This paper is concerned with the design, development, and autonomous flight testing of the GT Lama indoor Unmanned Aerial System (UAS). The GT Lama is a fully autonomous rotorcraft UAS capable of indoor area exploration. It weighs around 1.3 lbs (600 gms), has a width of about 27.6 inches (70 cm), and costs less than USD 900. The GT Lama employs only five off-the-shelf, extremely low-cost range sensors for navigation. The GT Lama does not rely on other expensive and sophisticated sensors, including inertial measurement units, Laser based range scanners, and GPS. The GT Lama achieves this by using simple wall following logic to ensure that maximum perimeter of an indoor environment is explored in a reasonable amount of time. The GT Lama hardware, and the Guidance, Navigation, and Control (GNC) algorithms used are discussed in detail. The details of a MATLAB based method that facilitates rapid in flight validation of GNC algorithms on real flight hardware is also discussed. Results from flight tests as the GT Lama autonomously explores indoor environments are presented.

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Georgia Tech Aerial Robotics Team: 2009 International Aerial Robotics Competition Entry

2009-07 , Chowdhary, Girish , Christmann, Hans Claus , Johnson, Eric N. , Salaün, Erwan , Sobers, D. Michael Jr.

This paper examines the use of low-cost range and target identification sensors on a stable flying vehicle for suitability in solving the 5th Mission proposed for the 2009 International Aerial Robotics Competition. The ability for vehicles to navigate unknown environments is critical for autonomous operation. Mapping of a vehicle's environment and self-localization within that environment are especially difficult for an Unmanned Aerial Vehicle (UAV) due to the complexity of UAV attitude and motion dynamics. Using a stable vehicle platform and taking advantage of the geometric structure typical of most indoor environments reduces the complexity of the localization and mapping problem to the point that wall and obstacle location can be determined using low-cost range sensors. Target identification is accomplished remotely using an onboard video camera with a radio transmitter. Thus complex and time-consuming image processing routines are run on a more powerful computer, enabling further miniaturization of the flight vehicle.

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Indoor Navigation for Unmanned Aerial Vehicles

2009-08 , Sobers, D. Michael Jr. , Chowdhary, Girish , Johnson, Eric N.

The ability for vehicles to navigate unknown environments is critical for autonomous operation. Mapping of a vehicle's environment and self-localization within that environment are especially difficult for an Unmanned Aerial Vehicle (UAV) due to the complexity of UAV attitude and motion dynamics, as well as interference from external influences such as wind. By using a stable vehicle platform and taking advantage of the geometric structure typical of most indoor environments, the complexity of the localization and mapping problem can be reduced. Interior wall and obstacle location can be measured using low-cost range sensors. Relative vehicle location within the mapped environment can then be determined. By alternating between mapping and localization, a vehicle can explore its environment autonomously. This paper examines available low-cost range sensors for suitability in solving the mapping and localization problem. A control system and navigation algorithm are developed to perform mapping of indoor environments and localization. Simulation and experimental results are provided to determine feasibility of the proposed approach to indoor navigation.

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Indoor Navigation for Unmanned Aerial Vehicles

2009-08 , Sobers, D. Michael Jr. , Chowdhary, Girish , Johnson, Eric N.

The ability for vehicles to navigate unknown environments is critical for autonomous operation. Mapping of a vehicle's environment and self-localization within that environ- ment are especially difficult for an Unmanned Aerial Vehicle (UAV) due to the complexity of UAV attitude and motion dynamics, as well as interference from external influences such as wind. By using a stable vehicle platform and taking advantage of the geometric structure typical of most indoor environments, the complexity of the localization and mapping problem can be reduced. Interior wall and obstacle location can be measured using low-cost range sensors. Relative vehicle location within the mapped environment can then be determined. By alternating between mapping and localization, a vehicle can explore its environment autonomously. This paper examines available low-cost range sensors for suitability in solving the mapping and localization problem. A control system and navigation algorithm are developed to perform mapping of indoor environments and localization. Simulation and experimental results are provided to determine feasibility of the proposed approach to indoor navigation.

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