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Flight Controller Synthesis Via Deep Reinforcement Learning
[article]
2019
arXiv
pre-print
Traditional control methods are inadequate in many deployment settings involving control of Cyber-Physical Systems (CPS). In such settings, CPS controllers must operate and respond to unpredictable interactions, conditions, or failure modes. Dealing with such unpredictability requires the use of executive and cognitive control functions that allow for planning and reasoning. Motivated by the sport of drone racing, this dissertation addresses these concerns for state-of-the-art flight control by
arXiv:1909.06493v1
fatcat:bg3es6bonbbr5ehrxpniyqj3x4