A GENERIC DECISION MAKING FRAMEWORK FOR AUTONOMOUS SYSTEMS

• Main Author: Lange, Connor
• Format: Others
• Published: DigitalCommons@CalPoly 2013
• Subjects: framework; CubeSat; PolySat; satellite; autonomous; Artificial Intelligence and Robotics; Space Vehicles
• Online Access: https://digitalcommons.calpoly.edu/theses/992; https://digitalcommons.calpoly.edu/cgi/viewcontent.cgi?article=2059&context=theses

With the rising popularity of small satellites, such as CubeSats, many smaller institutions previously incapable of developing and deploying a spacecraft have starting to do so. Institutions with a history of space flight, such as NASA JPL, have begun to put projects on CubeSats that would normally fly on much larger satellites. As a result, the institutions with space flight heritage have begun to port spacecraft software that was previously designed for much larger and more complex satellites to the CubeSat platform. Unfortunately for universities, who are the majority of all institutions devel- oping CubeSats, these ported systems are too large and complex to be a practical control solution. Student teams have a high turnover rate due to graduation and when a student becomes an expert on the control system, they graduate; most students get a maximum of two or three years of experience before graduating. This thesis proposes the Generic Decision Making Framework for Autonomous Systems (GDMFAS) as an accessible, easily extensible, component-based executive system architecture. The architecture is designed for Linux distributions, including the custom Linux distribution used by PolySat, and is implemented using C++. The proposed framework provides much of the same functionality as systems designed for larger satellites in a smaller, more straightforward pack- age, which includes both scheduling and executive components. This thesis also provides validation for the prototype implementation and evaluates the system according to six metrics. The metric analysis for this work is then compared with the metric analyses of previous works.