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Unmanned Aerial Vehicle Research Facility
Unmanned Aerial Vehicle Research Facility
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ItemIntegrated Guidance Navigation and Control for a Fully Autonomous Indoor UAS(Georgia Institute of Technology, 2011-08) Chowdhary, Girish ; Sobers, D. Michael, Jr. ; Pravitra, Chintasid ; Christmann, Hans Claus ; Wu, Allen ; Hashimoto, Hiroyuki ; Ong, Chester ; Kalghatgi, Roshan ; Johnson, Eric N.This paper describes the details of a Quadrotor miniature unmanned aerial system capable of autonomously exploring cluttered indoor areas without relying on any external navigational aids such as GPS. A streamlined Simultaneous Localization and Mapping (SLAM) algorithm is implemented onboard the vehicle to fuse information from a scanning laser range sensor, an inertial measurement unit, and an altitude sonar to provide relative position, velocity, and attitude information. This state information, with a self-generated map, is used to implement a frontier-based exhaustive search of an indoor environment. To ensure the SLAM algorithm has sufficient information to form a reliable solution, the guidance algorithm ensures the vehicle approaches frontier waypoints through a path that remains within sensor range of indoor structures. Along with a detailed description of the system, simulation and hardware testing results are presented.
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ItemGeorgia 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.
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ItemNetwork Discovery: An Estimation Based Approach(Georgia Institute of Technology, 2011-06) Chowdhary, Girish ; Egerstedt, Magnus B. ; Johnson, Eric N.We consider the unaddressed problem of network discovery, in which, an agent attempts to formulate an estimate of the global network topology using only locally available information. We show that under two key assumptions, the network discovery problem can be cast as a parameter estimation problem. Furthermore, we show that some form of excitation must be present in the network to be able to converge to a solution. The performance of two methods for solving the network discovery problem is evaluated in simulation.
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ItemFlight Testing of Nap of-the-Earth Unmanned Helicopter Systems(Georgia Institute of Technology, 2011-05) Johnson, Eric N. ; Mooney, John G. ; Ong, Chester ; Sahasrabudhe, Vineet ; Hartman, JonathanThis paper describes recent results from a partnership between the Sikorsky Aircraft Corporation and the Georgia Institute of Technology to develop, improve, and flight test a sensor, guidance, navigation, control, and real-time flight path optimization system to support high performance nap-of-the-Earth helicopter flight. The emphasis here is on optimization for a combination of low height above terrain/obstacles and high speeds. Multiple methods for generating the desired flight path were evaluated, including (1) a simple processing of each laser scan; and (2) a potential field based method. Simulation and flight test results have been obtained utilizing an onboard laser scanner to detect terrain and obstacles while flying at low altitude, and have successfully demonstrated obstacle avoidance in a realistic semi-urban environment at speeds up to 40 ft/s while maintaining a miss distance of 50 ft horizontally and vertically. These results indicate that the technical approach is sound, paving the way for testing of even lower altitudes, higher speeds, and more aggressive maneuvering in future work.
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ItemA Simulation Engine to Predict Multi-Agent Work in Complex, Dynamic, Heterogeneous Systems(Georgia Institute of Technology, 2011-02) Pritchett, Amy R. ; Christmann, Hans Claus ; Bigelow, Matthew S.This paper documents a simulation engine developed to accurately and efficiently simulate work by multiple agents in complex dynamic systems. Agents (human or mechanical) are modeled as responding to, and changing, their environment by executing the actions that get and set the value of resources in the environment. Each action comprises the processes that need to be evaluated at the same time by the same agent, which are used to reference (get) resources, consider them according to simple or complicated processes, and then interact back on the environment by setting resources appropriately. This paper specifically addresses timing within the simulation. The simplest approach would update all actions at the smallest unit of conceivable time, an approach that is not only computationally inefficient, but also not an accurate representation of situated behavior. Instead, every action declares its next update time as required to accurately model its internal dynamics and the simulation engine executes them asynchronously. Thus, an action and the resources it ’gets’ from the environment are not inherently contemporary; instead, each action also specifies, for each resource value that it gets, the quality of service required in terms of its temporal currency. This reflects dynamics of the real processes being simulated: when, in actual operations, would the environment be sampled, and how accurately must its state be known? Additionally, this also reflects dynamics of environmental resources how often (or how fast) does each inherently change? Using these constructs, the list of actions to be simulated are sorted by the simulation engine according to their next update time. Each action, when its time comes, is given to their agent model to be executed, and then is sorted back into the action list according to its self-reported next update time. Thus, actions are each updated when they need to be. In situations where, for example, action Y needs to get a resource which, because action X has not set it recently, does not meet action Ys required Quality of Service. The simulation engine will invoke action X immediately before action Y, mimicking cases in the real system where one process calls on another to establish the conditions it needs. The presented simulation engine is a complete redevelopment, designed and written from scratch at the Cognitive Engineering Center at the Georgia Institute of Technology.
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ItemVisibility Cues for Communication Aware Guidance in Cluttered Environments(Georgia Institute of Technology, 2011) Christmann, Hans Claus ; Johnson, Eric N.This paper presents the usage of visibility based guidance cues in order to find waypoints useful for maintaining communication in a multi UAV (Uninhabited Aerial Vehicle), single operator system. Based upon the overlay of visibility graphs (for radio communication) and Voronoi diagrams (for maximum clearance motion paths), the paper presents simulations of three staged methods, allowing the computation of waypoints suitable for establishing a potential multi-hop connection between an operator and a primary UAV in an urban or otherwise cluttered environment. The methods present generic solutions for 2D planes, ensuring applicability for indoor, outdoor, and other structured environments through a potential interconnection of several non-coplanar 2D planes. The presented methods increase in computational complexity as they are capable of handling more complex scenarios. However, the presented methods are overall still deemed computationally acceptable and present themselves as good candidates for onboard implementation on vehicles with limited computational power.
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ItemHigh Performance Nap-of-the-Earth Unmanned Helicopter Flight(Georgia Institute of Technology, 2011) Johnson, Eric N. ; Mooney, John G. ; Ong, Chester ; Sahasrabudhe, Vineet ; Hartman, JonathanThis paper describes recent results from a partnership between the Sikorsky Aircraft Corporation and the Georgia Institute of Technology to develop, improve, and flight test a sensor, guidance, navigation, control, and real-time flight path optimization system to support high performance nap-of-the-Earth helicopter flight. The emphasis here is on optimization for a combination of low height above terrain/obstacles and high speeds. Multiple methods for generating the desired flight path were evaluated, including (1) a simple processing of each laser scan; and (2) a potential field based method. Simulation and flight test results have been obtained utilizing an onboard laser scanner to detect terrain and obstacles while flying at low altitude, and have successfully demonstrated obstacle avoidance at speeds up to 40 ft/s while maintaining a miss distance of 50 ft horizontally and vertically. These results indicate that the technical approach is sound, paving the way for testing of even lower altitudes, higher speeds, and more aggressive maneuvering in future work.