Design, development and applications of a framework for autonomous vehicle operations
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The main objective of the current dissertation is to develop a "Plug and Play" autopilot. We present a systematic approach to decouple controller and filter design from hardware selection. This approach also addresses the performance decay due to hardware limitations. The outcome of this work is an integrated environment to develop, validate, and test algorithms to be used on flight controllers. The dynamic model of an off-the-shelf radio controlled airplane is derived. A controller is developed for the aircraft and it is implemented within the proposed framework. The framework and the controller developed are validated using hardware-in-the-loop simulation. A physical experiment with an autonomous ground vehicle is performed to test the autopilot and algorithms before test flights are performed. Finally a test flight is performed using a Great Planes Funster. A novel microsatellite attitude controller is presented. This controller is also developed and implemented using the approach presented in this dissertation. A satellite attitude hybrid simulator is presented and its design is discussed. An experimental apparatus to test the controller in a microgravity environment is constructed and discussed. Finally a set of experiments that demonstrate how the framework can be integrated into commercially available autopilots and vehicles is presented. First an off-the-shelf quad-rotor that integrates a look-down camera is used to perform visual navigation and landing. Second, a rover and a quad-rotor are used on a cooperative schema. The rover follows a route and the quad-rotor escorts it. The third experiment presents a popular autopilot on a surveillance mission. For this mission the airplane is equipped not only with the autopilot and radio link, but also with a video system. The video system consists of a camera and a radio link. These experimental results demonstrate the utility of the proposed framework in enhancing the capabilities of off-the-shelf autopilots and vehicles while simultaneously simplifying mission preparation and execution.