| A probabilistic particle-control approximation of chance-constrained stochastic predictive control L Blackmore, M Ono, A Bektassov, BC Williams IEEE transactions on Robotics 26 (3), 502-517, 2010 | 267 | 2010 |
| Chance-constrained optimal path planning with obstacles L Blackmore, M Ono, BC Williams IEEE Transactions on Robotics 27 (6), 1080-1094, 2011 | 190 | 2011 |
| Convex chance constrained predictive control without sampling L Blackmore, M Ono AIAA Guidance, Navigation, and Control Conference, 5876, 2009 | 148 | 2009 |
| Iterative risk allocation: A new approach to robust model predictive control with a joint chance constraint M Ono, BC Williams 2008 47th IEEE Conference on Decision and Control, 3427-3432, 2008 | 127 | 2008 |
| Real-time pricing mechanism for electricity market with built-in incentive for participation T Namerikawa, N Okubo, R Sato, Y Okawa, M Ono IEEE Transactions on Smart Grid 6 (6), 2714-2724, 2015 | 96 | 2015 |
| An Efficient Motion Planning Algorithm for Stochastic Dynamic Systems with Constraints on Probability of Failure. M Ono, BC Williams AAAI, 1376-1382, 2008 | 78 | 2008 |
| Probabilistic planning for continuous dynamic systems under bounded risk M Ono, BC Williams, L Blackmore Journal of Artificial Intelligence Research 46, 511-577, 2013 | 61 | 2013 |
| Chance-constrained dynamic programming with application to risk-aware robotic space exploration M Ono, M Pavone, Y Kuwata, J Balaram Autonomous Robots 39 (4), 555-571, 2015 | 57 | 2015 |
| Chance constrained finite horizon optimal control with nonconvex constraints M Ono, L Blackmore, BC Williams Proceedings of the 2010 American Control Conference, 1145-1152, 2010 | 52 | 2010 |
| Spoc: Deep learning-based terrain classification for mars rover missions B Rothrock, R Kennedy, C Cunningham, J Papon, M Heverly, M Ono AIAA SPACE 2016, 5539, 2016 | 51 | 2016 |
| Risk-aware planetary rover operation: Autonomous terrain classification and path planning M Ono, TJ Fuchs, A Steffy, M Maimone, J Yen 2015 IEEE aerospace conference, 1-10, 2015 | 48 | 2015 |
| Robust, optimal predictive control of jump markov linear systems using particles L Blackmore, A Bektassov, M Ono, BC Williams International Workshop on Hybrid Systems: Computation and Control, 104-117, 2007 | 45 | 2007 |
| Safe exploration and optimization of constrained mdps using gaussian processes A Wachi, Y Sui, Y Yue, M Ono Proceedings of the AAAI Conference on Artificial Intelligence 32 (1), 2018 | 38 | 2018 |
| Autonomous terrain classification with co-and self-training approach K Otsu, M Ono, TJ Fuchs, I Baldwin, T Kubota IEEE Robotics and Automation Letters 1 (2), 814-819, 2016 | 37 | 2016 |
| Joint chance-constrained model predictive control with probabilistic resolvability M Ono 2012 American Control Conference (ACC), 435-441, 2012 | 28 | 2012 |
| Robust, goal-directed plan execution with bounded risk M Ono | 23 | 2012 |
| Decentralized chance-constrained finite-horizon optimal control for multi-agent systems M Ono, BC Williams 49th IEEE Conference on Decision and Control (CDC), 138-145, 2010 | 22 | 2010 |
| Resisting adversarial attacks using gaussian mixture variational autoencoders P Ghosh, A Losalka, MJ Black Proceedings of the AAAI Conference on Artificial Intelligence 33, 541-548, 2019 | 18 | 2019 |
| Data-driven surface traversability analysis for Mars 2020 landing site selection M Ono, B Rothrock, E Almeida, A Ansar, R Otero, A Huertas, M Heverly 2016 IEEE Aerospace Conference, 1-12, 2016 | 16 | 2016 |
| An experimental study of the control of space robot teams assembling large flexible space structures P Boning, M Ono, T Nohara, S Dubowsky Proc. of the 9th International Symposium on Artificial Intelligence …, 2008 | 15 | 2008 |
Brian WilliamsProfessor of Aeronautics and Astronautics, Massachusetts Institute of TechnologyVerified email at mit.edu
