Jonathan DeCastro
Jonathan DeCastro
Toyota Research Institute
Verified email at - Homepage
Cited by
Cited by
User's guide for the commercial modular aero-propulsion system simulation (C-MAPSS)
DK Frederick, JA DeCastro, JS Litt
A modular aero-propulsion system simulation of a large commercial aircraft engine
J DeCastro, J Litt, D Frederick
44th AIAA/ASME/SAE/ASEE joint propulsion conference & exhibit, 4579, 2008
Reactive mission and motion planning with deadlock resolution avoiding dynamic obstacles
J Alonso-Mora, JA DeCastro, V Raman, D Rus, H Kress-Gazit
Autonomous Robots 42, 801-824, 2018
DiversityGAN: Diversity-aware vehicle motion prediction via latent semantic sampling
X Huang, SG McGill, JA DeCastro, L Fletcher, JJ Leonard, BC Williams, ...
IEEE Robotics and Automation Letters 5 (4), 5089-5096, 2020
Robust fault diagnosis of aircraft engines: A nonlinear adaptive estimation-based approach
X Zhang, L Tang, J DeCastro
IEEE Transactions on Control Systems Technology 21 (3), 861-868, 2012
Rate-based model predictive control of turbofan engine clearance
JA DeCastro
Journal of propulsion and power 23 (4), 804-813, 2007
Collision-Free Reactive Mission and Motion Planning for Multi-Robot Systems
JA DeCastro, J Alonso-Mora, V Raman, D Rus, H Kress-Gazit
Filtering and prediction techniques for model-based prognosis and uncertainty management
L Tang, J DeCastro, G Kacprzynski, K Goebel, G Vachtsevanos
2010 prognostics and system health management conference, 1-10, 2010
Vehicle trajectory prediction using generative adversarial network with temporal logic syntax tree features
X Li, G Rosman, I Gilitschenski, CI Vasile, JA DeCastro, S Karaman, ...
IEEE Robotics and Automation Letters 6 (2), 3459-3466, 2021
A recursive receding horizon planning for unmanned vehicles
B Zhang, L Tang, J DeCastro, MJ Roemer, K Goebel
IEEE Transactions on Industrial Electronics 62 (5), 2912-2920, 2014
User's guide for the commercial modular aero-propulsion system simulation (c-mapss): Version 2
Y Liu, DK Frederick, JA DeCastro, JS Litt, WW Chan
Synthesis of Nonlinear Continuous Controllers for Verifiably-Correct High-Level, Reactive Behaviors
JA DeCastro, H Kress-Gazit
International Journal of Robotics Research, 2014
Autonomous vehicle battery state-of-charge prognostics enhanced mission planning
B Zhang, L Tang, J DeCastro, M Roemer, K Goebel
International Journal of Prognostics and Health Management 5 (2), 2014
A testbed for real-time autonomous vehicle PHM and contingency management applications
L Tang, E Hettler, B Zhang, J DeCastro
Annual Conference of the PHM Society 3 (1), 2011
Development of a numerical model for high-temperature shape memory alloys
JA DeCastro, KJ Melcher, RD Noebe, DJ Gaydosh
Smart Materials and Structures 16 (6), 2080, 2007
Guaranteeing reactive high-level behaviors for robots with complex dynamics
JA DeCastro, H Kress-Gazit
2013 IEEE/RSJ International Conference on Intelligent Robots and Systems …, 2013
The logical options framework
B Araki, X Li, K Vodrahalli, J DeCastro, M Fry, D Rus
International Conference on Machine Learning, 307-317, 2021
Compositional and contract-based verification for autonomous driving on road networks
L Liebenwein, W Schwarting, CI Vasile, J DeCastro, J Alonso-Mora, ...
Robotics Research: The 18th International Symposium ISRR, 163-181, 2020
A unified nonlinear adaptive approach for detection and isolation of engine faults
L Tang, X Zhang, JA DeCastro, L Farfan-Ramos, DL Simon
Turbo Expo: Power for Land, Sea, and Air 43987, 143-153, 2010
Exact nonlinear filtering and prediction in process model-based prognostics
JA DeCastro, L Tang, KA Loparo, K Goebel, G Vachtsevanos
Annual Conference of the PHM Society 1 (1), 2009
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