Robust Intelligent Sensing and Control Multi Agent Analysis Platform for Research and Education

The aim of this thesis is the development and implementation of a controlled testing platform for the Robust Intelligent Sensing and Controls (RISC) Lab at Utah State University (USU). This will be an open source adaptable expandable robotics platform usable for both education and research. This differs from the many other platforms developed in that the entire platform software will be made open source. This open source software will encourage collaboration among other universities and enable researchers to essentially pick up where others have left off without the necessity of replicating months or even years of work. The expected results of this research will create a foundation for diverse robotics investigation at USU as well as enable attempts at novel methods of control, estimation and optimization. This will also contribute a complete software testbed setup to the already vibrant robotics open source research community. This thesis first outlines the platform setup and novel developments therein. The second stage provides an example of how this has been used in education, providing an example curriculum implementing modern control techniques. The third section provides some exploratory research in trajectory control and state estimation of the tip of an inverted pendulum atop a small unmanned aerial vehicle as well as bearing-only cooperative localization experimentation. Finally, a conclusion and future work is discussed