Articles with public access mandates - Kerianne HobbsLearn more
Not available anywhere: 6
Run time assured reinforcement learning for safe satellite docking
K Dunlap, M Mote, K Delsing, KL Hobbs
Journal of Aerospace Information Systems 20 (1), 25-36, 2023
Mandates: US Department of Defense
Safe reinforcement learning benchmark environments for aerospace control systems
UJ Ravaioli, J Cunningham, J McCarroll, V Gangal, K Dunlap, KL Hobbs
2022 IEEE Aerospace Conference (AERO), 1-20, 2022
Mandates: US Department of Defense
Formal specification and analysis approaches for spacecraft attitude control requirements
KH Gross
2017 IEEE Aerospace Conference, 1-11, 2017
Mandates: US Department of Defense
Guaranteeing Safety via Active-Set Invariance Filters for Multi-Agent Space Systems with Coupled Dynamics*
M Hibbard, U Topcu, K Hobbs
2022 American Control Conference (ACC), 430-436, 2022
Mandates: US Department of Defense
Formal verification of system states for spacecraft automatic maneuvering
KL Hobbs, I Perez, A Fifarek, EM Feron
AIAA Scitech 2019 Forum, 1187, 2019
Mandates: US National Aeronautics and Space Administration
Bridging the Gap: Applying Argument to MIL-HDBK-516C Certification of a Neural Network Controller Guarded by ASIF Run Time Assurance
J Rowanhill, KL Hobbs, A Zutshi, AB Hocking
2023 IEEE/AIAA 42nd Digital Avionics Systems Conference (DASC), 1-9, 2023
Mandates: US Department of Defense
Available somewhere: 9
Improved geometric path enumeration for verifying relu neural networks
S Bak, HD Tran, K Hobbs, TT Johnson
Computer Aided Verification: 32nd International Conference, CAV 2020, Los …, 2020
Mandates: US National Science Foundation, US Department of Defense
Comparing run time assurance approaches for safe spacecraft docking
K Dunlap, M Hibbard, M Mote, K Hobbs
IEEE Control Systems Letters 6, 1849-1854, 2021
Mandates: US Department of Defense
Space trusted autonomy readiness levels
KL Hobbs, JB Lyons, MS Feather, BP Bycroft, S Phillips, M Simon, ...
2023 IEEE Aerospace Conference, 1-17, 2023
Mandates: US Department of Defense, US National Aeronautics and Space Administration
Evaluation of neural network verification methods for air-to-air collision avoidance
D Manzanas Lopez, TT Johnson, S Bak, HD Tran, KL Hobbs
Journal of Air Transportation 31 (1), 1-17, 2023
Mandates: US National Science Foundation, US Department of Defense
Verification of neural network compression of ACAS Xu lookup tables with star set reachability
D Manzanas Lopez, T Johnson, HD Tran, S Bak, X Chen, KL Hobbs
AIAA Scitech 2021 Forum, 0995, 2021
Mandates: US National Science Foundation, US Department of Defense
Ablation study of how run time assurance impacts the training and performance of reinforcement learning agents
N Hamilton, K Dunlap, TT Johnson, KL Hobbs
2023 IEEE 9th International Conference on Space Mission Challenges for …, 2023
Mandates: US Department of Defense
A universal framework for generalized run time assurance with jax automatic differentiation
UJ Ravaioli, K Dunlap, K Hobbs
2023 American Control Conference (ACC), 4264-4269, 2023
Mandates: US Department of Defense
Systems theoretic process analysis of a run time assured neural network control system
KL Hobbs, B Heiner, L Busse, K Dunlap, J Rowanhill, AB Hocking, ...
AIAA SciTech 2023 Forum, 2664, 2023
Mandates: US Department of Defense
Reinforcement Learning Heuristics for Aerospace Control Systems
PK Robinette, BK Heiner, U Ravaioli, N Hamilton, TT Johnson, KL Hobbs
2022 IEEE Aerospace Conference (AERO), 1-12, 2022
Mandates: US Department of Defense
Publication and funding information is determined automatically by a computer program