Ensuring Quadrotor Safety Through Geofencing with Run Time Assurance



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Safety assurance in autonomous safety critical aerospace systems has become an increasingly relevant area of study as mission objectives, hardware, and even human lives become endangered when integrating  complex and intelligent control system designs. With this rise of control and mission complexity for autonomous aerospace systems, a balance must be struck between mission objectives and system safety. A recent method of creating this balance has come to be known as online safety assurance techniques or Run  Time Assurance (RTA), a control intervention method designed separately from a  system's primary controller to assure safety in real time. The research presented in this thesis analyzes two RTA intervention methods, a switching-based filter known as the Simplex method, and an optimization-based filter known as the ASIF method, in the control of simulated quadcopters to create an impassible safety cube or 'geofence' in each of the quadcopter's reference axes. The  safety barriers created for the geofence are formally defined using the nascent topic of  Control Barrier Functions (CBFs), independently defined for each flight direction (X, Y,  Z), and implemented with Python, the primary language of the simulated environment.  This thesis will conclude with a comparison of the two RTA methods and the  effectiveness of their implementation on different quadcopter mission objectives.



Run Time Assurance, RTA, Control Barrier Function, CBF, Safety, Drone, Geofence, Mechanical Engineering, Aerospace Engineering