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dc.contributor.authorKoch, Williamen_US
dc.contributor.authorMancuso, Renatoen_US
dc.contributor.authorBestavros, Azeren_US
dc.date.accessioned2020-06-16T15:52:15Z
dc.date.available2020-06-16T15:52:15Z
dc.date.issued2019-01-19
dc.identifierhttp://arxiv.org/abs/1901.06553v1
dc.identifier.citationWilliam Koch, Renato Mancuso, Azer Bestavros. "Neuroflight: next generation flight control firmware." 7 pages. http://arxiv.org/abs/1901.06553v1
dc.identifier.urihttps://hdl.handle.net/2144/41205
dc.description.abstractLittle innovation has been made to low-level attitude flight control used by unmanned aerial vehicles, which still predominantly uses the classical PID controller. In this work we introduce Neuroflight, the first open source neuro-flight controller firmware. We present our toolchain for training a neural network in simulation and compiling it to run on embedded hardware. Challenges faced jumping from simulation to reality are discussed along with our solutions. Our evaluation shows the neural network can execute at over 2.67kHz on an Arm Cortex-M7 processor and flight tests demonstrate a quadcopter running Neuroflight can achieve stable flight and execute aerobatic maneuvers.en_US
dc.format.extent7 pagesen_US
dc.language.isoen_US
dc.publisherarXiven_US
dc.relation.ispartofComputing Research Repository
dc.subjectRoboticsen_US
dc.titleNeuroflight: next generation flight control firmwareen_US
dc.typeArticleen_US
dc.description.versionAccepted manuscripten_US
pubs.elements-sourcemanual-entryen_US
pubs.notesEmbargo: No embargoen_US
pubs.organisational-groupBoston Universityen_US
pubs.organisational-groupBoston University, Administrationen_US
pubs.organisational-groupBoston University, College of Arts & Sciencesen_US
pubs.organisational-groupBoston University, College of Arts & Sciences, Department of Computer Scienceen_US
pubs.publication-statusSubmitteden_US
dc.date.online2019-01-19
dc.identifier.orcid0000-0003-0798-8835 (Bestavros, Azer)
dc.identifier.mycv424606


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