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ORCIDMeeko M. K. Oishi
Meeko Mitsuko Oishi – Meeko Oishi
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2020 – today
- 2024
[j25]Vignesh Sivaramakrishnan
, Abraham P. Vinod, Meeko M. K. Oishi:
Convexified Open-Loop Stochastic Optimal Control for Linear Systems With Log-Concave Disturbances. IEEE Trans. Autom. Control. 69(2): 1249-1256 (2024)- [j24]Isabella Pacula, Meeko Oishi:
Open-Loop Chance Constrained Stochastic Optimal Control via the One-Sided Vysochanskij-Petunin Inequality. IEEE Trans. Autom. Control. 69(8): 5383-5395 (2024) - [j23]Harini Sridhar, Gaojian Huang, Adam J. Thorpe, Meeko Oishi, Brandon J. Pitts:
Characterizing the Effect of Mind Wandering on Braking Dynamics in Partially Autonomous Vehicles. ACM Trans. Cyber Phys. Syst. 8(3): 26:1-26:21 (2024) - [c73]Natalia Pavlasek, Sarah H. Q. Li, Behçet Açikmese, Meeko Oishi, Claus Danielson:
Blameless and Optimal Control under Prioritized Safety Constraints. ACC 2024: 2311-2317 - [c72]Adam J. Thorpe, Cyrus Neary, Franck Djeumou, Meeko M. K. Oishi, Ufuk Topcu:
Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control. ACC 2024: 3130-3137 - [i34]Vignesh Sivaramakrishnan, Rosalyn A. Devonport, Murat Arcak, Meeko M. K. Oishi:
Forward Reachability for Discrete-Time Nonlinear Stochastic Systems via Mixed-Monotonicity and Stochastic Order. CoRR abs/2407.03984 (2024) - 2023
- [c71]Adam J. Thorpe, Jake A. Gonzales, Meeko M. K. Oishi:
Data-Driven Stochastic Optimal Control Using Kernel Gradients. ACC 2023: 2548-2553 - [c70]Shawn Priore, Ali Bidram, Meeko Oishi:
Chance Constrained Stochastic Optimal Control for Linear Systems with Time Varying Random Plant Parameters. ACC 2023: 2599-2606 - [c69]Shawn Priore, Meeko Oishi:
Chance Constrained Stochastic Optimal Control for Linear Systems with a Time Varying Random Control Matrix. CCTA 2023: 599-604 - [c68]Shawn Priore, Meeko Oishi:
Stochastic Optimal Control For Gaussian Disturbances with Unknown Mean and Variance Based on Sample Statistics. CDC 2023: 2776-2783 - [c67]Chukwuemeka O. Ike, John T. Wen, Meeko M. K. Oishi, Lee K. Brown, A. Agung Julius:
Efficient Estimation of the Human Circadian Phase via Kalman Filtering. EMBC 2023: 1-6 - [c66]Joshua Pilipovsky, Vignesh Sivaramakrishnan, Meeko Oishi, Panagiotis Tsiotras:
Probabilistic Verification of ReLU Neural Networks via Characteristic Functions. L4DC 2023: 966-979 - [i33]Adam J. Thorpe, Cyrus Neary, Franck Djeumou, Meeko M. K. Oishi, Ufuk Topcu:
Physics-Informed Kernel Embeddings: Integrating Prior System Knowledge with Data-Driven Control. CoRR abs/2301.03565 (2023) - [i32]Shawn Priore, Meeko Oishi:
Chance Constrained Stochastic Optimal Control for Linear Systems with a Time Varying Random Control Matrix. CoRR abs/2302.01863 (2023) - [i31]Shawn Priore, Meeko Oishi:
Chance Constrained Stochastic Optimal Control for Arbitrarily Disturbed LTI Systems Via the One-Sided Vysochanskij-Petunin Inequality. CoRR abs/2303.12295 (2023) - [i30]Shawn Priore, Meeko Oishi:
Stochastic Optimal Control For Gaussian Disturbances with Unknown Mean and Variance Based on Sample Statistics. CoRR abs/2303.13036 (2023) - [i29]Shawn Priore, Meeko Oishi:
Chance Constrained Stochastic Optimal Control Based on Sample Statistics With Almost Surely Probabilistic Guarantees. CoRR abs/2303.16981 (2023) - [i28]Karthik Sivaramakrishnan, Vignesh Sivaramakrishnan, Meeko M. K. Oishi:
Stochastic Reachability of Discrete-Time Stochastic Systems via Probability Measures. CoRR abs/2304.00598 (2023) - 2022
- [j22]Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi:
State-based confidence bounds for data-driven stochastic reachability using Hilbert space embeddings. Autom. 138: 110146 (2022) - [j21]Mohammad Abdullah Al Faruque, Meeko Mitsuko Oishi:
Introduction to the Special Section on Selected Papers from ICCPS 2021. ACM Trans. Cyber Phys. Syst. 6(4): 29e:1-29e:3 (2022) - [j20]Abraham P. Vinod, Adam J. Thorpe, Philip A. Olaniyi, Tyler H. Summers, Meeko M. K. Oishi:
Sensor Selection for Dynamics-Driven User-Interface Design. IEEE Trans. Control. Syst. Technol. 30(1): 71-84 (2022) - [c65]Shawn Priore, Christopher Petersen, Meeko Oishi:
Approximate Quantiles for Stochastic Optimal Control of LTI Systems with Arbitrary Disturbances. ACC 2022: 1814-1821 - [c64]Vignesh Sivaramakrishnan, Joshua Pilipovsky, Meeko Oishi, Panagiotis Tsiotras:
Distribution Steering for Discrete-Time Linear Systems with General Disturbances using Characteristic Functions. ACC 2022: 4183-4190 - [c63]Adam J. Thorpe, Meeko Oishi:
SOCKS: A Stochastic Optimal Control and Reachability Toolbox Using Kernel Methods. HSCC 2022: 21:1-21:12 - [c62]Adam J. Thorpe, Thomas Lew, Meeko Oishi, Marco Pavone:
Data-Driven Chance Constrained Control using Kernel Distribution Embeddings. L4DC 2022: 790-802 - [i27]Adam J. Thorpe, Thomas Lew, Meeko M. K. Oishi, Marco Pavone:
Data-Driven Chance Constrained Control using Kernel Distribution Embeddings. CoRR abs/2202.04193 (2022) - [i26]Adam J. Thorpe, Meeko M. K. Oishi:
SOCKS: A Stochastic Optimal Control and Reachability Toolbox Using Kernel Methods. CoRR abs/2203.06290 (2022) - [i25]Kendric R. Ortiz, Adam J. Thorpe, AnaMaria Perez, Maya Luster, Brandon J. Pitts, Meeko Oishi:
Characterizing Within-Driver Variability in Driving Dynamics During Obstacle Avoidance Maneuvers. CoRR abs/2206.01331 (2022) - [i24]Adam J. Thorpe, Jake A. Gonzales, Meeko M. K. Oishi:
Data-Driven Stochastic Optimal Control Using Kernel Gradients. CoRR abs/2209.09205 (2022) - [i23]Shawn Priore, Ali Bidram, Meeko Oishi:
Optimal Control Strategy for Linear Systems with Time Varying Random Plant Parameters. CoRR abs/2210.09468 (2022) - [i22]Shawn Priore, Christopher Petersen, Meeko Oishi:
Approximate Stochastic Optimal Control for Linear Time Invariant Systems with Heavy-tailed Disturbances. CoRR abs/2210.09479 (2022) - [i21]Joshua Pilipovsky, Vignesh Sivaramakrishnan, Meeko M. K. Oishi, Panagiotis Tsiotras:
Probabilistic Verification of ReLU Neural Networks via Characteristic Functions. CoRR abs/2212.01544 (2022) - 2021
- [j19]Abraham P. Vinod, Meeko M. K. Oishi:
Stochastic reachability of a target tube: Theory and computation. Autom. 125: 109458 (2021) - [j18]Joseph D. Gleason, Abraham P. Vinod, Meeko M. K. Oishi:
Lagrangian approximations for stochastic reachability of a target tube. Autom. 128: 109546 (2021) - [j17]Abraham P. Vinod, Meeko M. K. Oishi:
Probabilistic Occupancy via Forward Stochastic Reachability for Markov Jump Affine Systems. IEEE Trans. Autom. Control. 66(7): 3068-3083 (2021) - [c61]Adam J. Thorpe, Vignesh Sivaramakrishnan, Meeko M. K. Oishi:
Approximate Stochastic Reachability for High Dimensional Systems. ACC 2021: 1287-1293 - [c60]Shawn Priore, Abraham P. Vinod, Vignesh Sivaramakrishnan, Christopher Petersen, Meeko Oishi:
Stochastic multi-satellite maneuvering with constraints in an elliptical orbit. ACC 2021: 4261-4268 - [c59]Adam J. Thorpe, Meeko M. K. Oishi:
Stochastic Optimal Control via Hilbert Space Embeddings of Distributions. CDC 2021: 904-911 - [c58]Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi:
SReachTools Kernel Module: Data-Driven Stochastic Reachability Using Hilbert Space Embeddings of Distributions. CDC 2021: 5073-5079 - [c57]Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi:
Learning Approximate Forward Reachable Sets Using Separating Kernels. L4DC 2021: 201-212 - [e1]Martina Maggio, James Weimer, Mohammad Al Farque, Meeko Oishi:
ICCPS '21: ACM/IEEE 12th International Conference on Cyber-Physical Systems, Nashville, Tennessee, USA, May 19-21, 2021. ACM 2021, ISBN 978-1-4503-8353-0 [contents] - [i20]Adam J. Thorpe, Meeko M. K. Oishi:
Stochastic Optimal Control via Hilbert Space Embeddings of Distributions. CoRR abs/2103.12759 (2021) - [i19]Shawn Priore, Christopher Petersen, Meeko Oishi:
Approximate Quantiles for Stochastic Optimal Control of LTI Systems with Arbitrary Disturbances. CoRR abs/2110.03040 (2021) - 2020
- [j16]Adam J. Thorpe, Meeko M. K. Oishi:
Model-Free Stochastic Reachability Using Kernel Distribution Embeddings. IEEE Control. Syst. Lett. 4(2): 512-517 (2020) - [j15]Vignesh Sivaramakrishnan, Meeko M. K. Oishi:
Fast, Convexified Stochastic Optimal Open-Loop Control for Linear Systems Using Empirical Characteristic Functions. IEEE Control. Syst. Lett. 4(4): 1048-1053 (2020) - [c56]Nathan Patrizi, Georgios Fragkos, Kendric R. Ortiz, Meeko Oishi, Eirini-Eleni Tsiropoulou:
A UAV-enabled Dynamic Multi-Target Tracking and Sensing Framework. GLOBECOM 2020: 1-6 - [i18]Somali Chaterji, Parinaz Naghizadeh, Muhammad Ashraful Alam, Saurabh Bagchi, Mung Chiang, David Corman, Brian J. Henz, Suman Jana, Na Li, Shaoshuai Mou, Meeko Oishi, Chunyi Peng, Tiark Rompf, Ashutosh Sabharwal, Shreyas Sundaram, James Weimer, Jennifer Weller:
Resilient Cyberphysical Systems and their Application Drivers: A Technology Roadmap. CoRR abs/2001.00090 (2020) - [i17]Abraham P. Vinod, Adam J. Thorpe, Philip A. Olaniyi, Tyler H. Summers, Meeko M. K. Oishi:
Trust-based user-interface design for human-automation systems. CoRR abs/2004.07176 (2020) - [i16]Vignesh Sivaramakrishnan, Abraham P. Vinod, Meeko M. K. Oishi:
Convexified Open-Loop Stochastic Optimal Control for Linear Non-Gaussian Systems. CoRR abs/2010.02101 (2020) - [i15]Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi:
Data-Driven Stochastic Reachability Using Hilbert Space Embeddings. CoRR abs/2010.08036 (2020) - [i14]Adam J. Thorpe, Kendric R. Ortiz, Meeko M. K. Oishi:
SReachTools Kernel Module: Data-Driven Stochastic Reachability Using Hilbert Space Embeddings of Distributions. CoRR abs/2011.10610 (2020)
2010 – 2019
- 2019
- [j14]Joseph D. Gleason, Meeko M. K. Oishi, John T. Wen, Agung Julius, Suguna Pappu, Howard Yonas:
Assessing circadian rhythms and entrainment via intracranial temperature after severe head trauma. Biomed. Signal Process. Control. 54 (2019) - [c55]Hossein Sartipizadeh, Abraham P. Vinod, Behçet Açikmese, Meeko Oishi:
Voronoi Partition-based Scenario Reduction for Fast Sampling-based Stochastic Reachability Computation of Linear Systems. ACC 2019: 37-44 - [c54]Abraham P. Vinod, Vignesh Sivaramakrishnan, Meeko M. K. Oishi:
Piecewise-Affine Approximation-Based Stochastic Optimal Control with Gaussian Joint Chance Constraints. ACC 2019: 2942-2949 - [c53]Vignesh Sivaramakrishnan, Omanshu Thapliyal, Abraham P. Vinod, Meeko Oishi, Inseok Hwang:
Predicting Mode Confusion Through Mixed Integer Linear Programming. CDC 2019: 2442-2448 - [c52]Milad Khaledyan, Abraham P. Vinod, Meeko Oishi, John A. Richards:
Optimal Coverage Control and Stochastic Multi-Target Tracking. CDC 2019: 2467-2472 - [c51]Joseph D. Gleason, Abraham P. Vinod, Meeko M. K. Oishi:
The Maximal Hitting-Time Stochastic Reachability Problem. CDC 2019: 7266-7272 - [c50]Abraham P. Vinod, Meeko M. K. Oishi:
Affine controller synthesis for stochastic reachability via difference of convex programming. CDC 2019: 7273-7280 - [c49]Alessandro Abate, Henk A. P. Blom, Nathalie Cauchi, Kurt Degiorgio, Martin Fränzle, Ernst Moritz Hahn, Sofie Haesaert, Hao Ma, Meeko Oishi, Carina Pilch, Anne Remke, Mahmoud Salamati, Sadegh Soudjani, Birgit van Huijgevoort, Abraham P. Vinod:
ARCH-COMP19 Category Report: Stochastic Modelling. ARCH@CPSIoTWeek 2019: 62-102 - [c48]Abraham P. Vinod, Joseph D. Gleason, Meeko M. K. Oishi:
SReachTools: a MATLAB stochastic reachability toolbox. HSCC 2019: 33-38 - [c47]Abraham P. Vinod, Joseph D. Gleason, Meeko M. K. Oishi:
SReachTools: A MATLAB stochastic reachability toolbox: demo abstract. HSCC 2019: 264-265 - [c46]Abraham P. Vinod, Vignesh Sivaramakrishnan, Meeko M. K. Oishi:
Sampling-free enforcement of non-gaussian chance constraints via fourier transforms. SNR 2019: 9-11 - [i13]Adam J. Thorpe, Meeko M. K. Oishi:
Model-Free Stochastic Reachability Using Kernel Distribution Embeddings. CoRR abs/1908.00697 (2019) - [i12]Adam J. Thorpe, Vignesh Sivaramakrishnan, Meeko M. K. Oishi:
Stochastic Reachability for Systems up to a Million Dimensions. CoRR abs/1910.10818 (2019) - 2018
- [c45]Alessandro Abate, Henk A. P. Blom, Nathalie Cauchi, Sofie Haesaert, Arnd Hartmanns, Kendra Lesser, Meeko Oishi, Vignesh Sivaramakrishnan, Sadegh Soudjani, Cristian Ioan Vasile, Abraham P. Vinod:
ARCH-COMP18 Category Report: Stochastic Modelling. ARCH@ADHS 2018: 71-103 - [c44]Abraham P. Vinod, Baisravan HomChaudhuri, Christoph Hintz, Anup Parikh, Stephen P. Buerger, Meeko M. K. Oishi, Greg Brunson, Shakeeb Ahmad, Rafael Fierro:
Multiple Pursuer-Based Intercept via Forward Stochastic Reachability. ACC 2018: 1559-1566 - [c43]Abraham P. Vinod, Sean Rice, Yuanqi Mao, Meeko M. K. Oishi, Behçet Açikmese:
Stochastic Motion Planning Using Successive Convexification and Probabilistic Occupancy Functions. CDC 2018: 4425-4432 - [c42]Abraham P. Vinod, Meeko M. K. Oishi:
Scalable Underapproximative Verification of Stochastic LTI Systems using Convexity and Compactness. HSCC 2018: 1-10 - [i11]Abraham P. Vinod, Baisravan HomChaudhuri, Meeko M. K. Oishi:
Probabilistic Occupancy Function and Sets Using Forward Stochastic Reachability for Rigid-Body Dynamic Obstacles. CoRR abs/1803.07180 (2018) - [i10]Abraham P. Vinod, Meeko M. K. Oishi:
Stochastic reachability of a target tube: Theory and computation. CoRR abs/1810.05217 (2018) - [i9]Joseph D. Gleason, Abraham P. Vinod, Meeko M. K. Oishi:
Lagrangian Approximations for Stochastic Reachability of a Target Tube. CoRR abs/1810.07118 (2018) - [i8]Hossein Sartipizadeh, Abraham P. Vinod, Behçet Açikmese, Meeko Oishi:
Voronoi Partition-based Scenario Reduction for Fast Sampling-based Stochastic Reachability Computation of LTI Systems. CoRR abs/1811.03643 (2018) - 2017
- [j13]Abraham P. Vinod, Meeko M. K. Oishi:
Scalable Underapproximation for the Stochastic Reach-Avoid Problem for High-Dimensional LTI Systems Using Fourier Transforms. IEEE Control. Syst. Lett. 1(2): 316-321 (2017) - [j12]Kendra Lesser, Meeko Oishi:
Approximate Safety Verification and Control of Partially Observable Stochastic Hybrid Systems. IEEE Trans. Autom. Control. 62(1): 81-96 (2017) - [j11]Nick Malone, Hao-Tien Chiang, Kendra Lesser, Meeko Oishi, Lydia Tapia:
Hybrid Dynamic Moving Obstacle Avoidance Using a Stochastic Reachable Set-Based Potential Field. IEEE Trans. Robotics 33(5): 1124-1138 (2017) - [c41]Baisravan HomChaudhuri, Abraham P. Vinod, Meeko M. K. Oishi:
Computation of forward stochastic reach sets: Application to stochastic, dynamic obstacle avoidance. ACC 2017: 4404-4411 - [c40]Joseph D. Gleason, Abraham P. Vinod, Meeko M. K. Oishi:
Underapproximation of reach-avoid sets for discrete-time stochastic systems via Lagrangian methods. CDC 2017: 4283-4290 - [c39]Joseph D. Gleason, Meeko Oishi, Michelle Simkulet, Arunas Tuzikas, Lee K. Brown, S. R. J. Brueck, Robert F. Karlicek:
A novel smart lighting clinical testbed. EMBC 2017: 4317-4320 - [c38]Abraham P. Vinod, Baisravan HomChaudhuri, Meeko M. K. Oishi:
Forward Stochastic Reachability Analysis for Uncontrolled Linear Systems using Fourier Transforms. HSCC 2017: 35-44 - [c37]Hao-Tien Lewis Chiang, Baisravan HomChaudhuri, Abraham P. Vinod, Meeko Oishi, Lydia Tapia:
Dynamic risk tolerance: Motion planning by balancing short-term and long-term stochastic dynamic predictions. ICRA 2017: 3762-3769 - [c36]Torin Adamson, Meeko Oishi, Hao-Tien Lewis Chiang, Lydia Tapia:
Busy beeway: a game for testing human-automation collaboration for navigation. MIG 2017: 9:1-9:6 - [i7]Abraham P. Vinod, Meeko M. K. Oishi:
Scalable Underapproximation for Stochastic Reach-Avoid Problem for High-Dimensional LTI Systems using Fourier Transforms. CoRR abs/1703.02135 (2017) - [i6]Joseph D. Gleason, Abraham P. Vinod, Meeko M. K. Oishi:
Underapproximation of Reach-Avoid Sets for Discrete-Time Stochastic Systems via Lagrangian Methods. CoRR abs/1704.03555 (2017) - 2016
- [j10]Meeko M. K. Oishi, Dawn M. Tilbury, Claire J. Tomlin:
Guest Editorial Special Section on Human-Centered Automation. IEEE Trans Autom. Sci. Eng. 13(1): 4-6 (2016) - [j9]Tasha M. Hammond, Neda Eskandari, Meeko M. K. Oishi:
Observability of User-Interfaces for Hybrid LTI Systems Under Collaborative Control: Application to Aircraft Flight Management Systems. IEEE Trans Autom. Sci. Eng. 13(1): 78-84 (2016) - [c35]Abraham P. Vinod, Tyler H. Summers, Meeko M. K. Oishi:
User-interface design for MIMO LTI human-automation systems through sensor placement. ACC 2016: 5276-5283 - [c34]Baisravan HomChaudhuri, Meeko Oishi, Matt Shubert, Morgan Baldwin, Richard Scott Erwin:
Computing reach-avoid sets for space vehicle docking under continuous thrust. CDC 2016: 3312-3318 - [c33]Joseph D. Gleason, Abraham P. Vinod, Meeko M. K. Oishi, Richard Scott Erwin:
Viable set approximation for linear-Gaussian systems with unknown, bounded variance. CDC 2016: 7049-7055 - [c32]Abraham P. Vinod, Yuqing Tang, Meeko M. K. Oishi, Katia P. Sycara, Christian Lebiere, Michael Lewis:
Validation of cognitive models for collaborative hybrid systems with discrete human input. IROS 2016: 3339-3346 - [i5]Baisravan HomChaudhuri, Abraham P. Vinod, Meeko M. K. Oishi:
Computation of forward stochastic reach sets: Application to stochastic, dynamic obstacle avoidance. CoRR abs/1610.03472 (2016) - [i4]Abraham P. Vinod, Baisravan Homchaudhuri, Meeko M. K. Oishi:
Forward stochastic reachability analysis for uncontrolled linear systems using Fourier Transforms. CoRR abs/1610.04550 (2016) - 2015
- [j8]Shahab Kaynama, Ian M. Mitchell, Meeko M. K. Oishi, Guy Albert Dumont:
Scalable Safety-Preserving Robust Control Synthesis for Continuous-Time Linear Systems. IEEE Trans. Autom. Control. 60(11): 3065-3070 (2015) - [c31]Carlos Gonzalez, Daniel Svenkeson, Diana Kim, Martin J. McKeown, Meeko Oishi:
Detection of manual tracking submovements in Parkinson's disease through hybrid optimization. ADHS 2015: 291-297 - [c30]Kendra Lesser, Meeko M. K. Oishi:
Computing probabilistic viable sets for partially observable systems using truncated gaussians and adaptive gridding. ACC 2015: 1505-1512 - [c29]Patricio Cruz, Meeko Oishi, Rafael Fierro:
Lift of a cable-suspended load by a quadrotor: A hybrid system approach. ACC 2015: 1887-1892 - [c28]Kendra Lesser, Meeko Oishi:
Finite state approximation for verification of partially observable stochastic hybrid systems. HSCC 2015: 159-168 - [c27]Hao-Tien Chiang, Nick Malone, Kendra Lesser, Meeko Oishi, Lydia Tapia:
Path-guided artificial potential fields with stochastic reachable sets for motion planning in highly dynamic environments. ICRA 2015: 2347-2354 - 2014
- [j7]Kendra Lesser, Meeko Oishi:
Reachability for partially observable discrete time stochastic hybrid systems. Autom. 50(8): 1989-1998 (2014) - [j6]Daniel Svenkeson, Bobby Sena, Meeko Oishi, Suguna Pappu, Howard Yonas:
A Novel Use of Transfer Function Estimation for Early Assessment of Brain Injury Outcome. IEEE Trans. Biomed. Eng. 61(9): 2413-2421 (2014) - [c26]Seyed Behzad Tabibian, Michael Lewis, Christian Lebiere, Nilanjan Chakraborty, Katia P. Sycara, Stefano Bennati, Meeko Oishi:
Towards a Cognitively-Based Analytic Model of Human Control of Swarms. AAAI Spring Symposia 2014 - [c25]Meeko M. K. Oishi:
Assessing information availability for user-interfaces of shared control systems under reference tracking. ACC 2014: 3474-3481 - [c24]Richard T. Meyer, Fabian Just, Raymond A. DeCarlo, Milos Zefran, Meeko Oishi:
Notch filter and MPC for powered wheelchair operation under Parkinson's tremor. ACC 2014: 4114-4120 - [c23]Trisha Biswas, Kendra Lesser, Rudra Dutta, Meeko M. K. Oishi:
Using linear system reliability to obtain theoretical understanding of wireless routing. GLOBECOM 2014: 1310-1316 - [c22]Trisha Biswas, Kendra Lesser, Rudra Dutta, Meeko M. K. Oishi:
Examining reliability of wireless multihop network routing with linear systems. HotSoS 2014: 19 - [c21]Nick Malone, Kendra Lesser, Meeko M. K. Oishi, Lydia Tapia:
Stochastic reachability based motion planning for multiple moving obstacle avoidance. HSCC 2014: 51-60 - [c20]Hao-Tien Chiang, Nick Malone, Kendra Lesser, Meeko M. K. Oishi, Lydia Tapia:
Aggressive Moving Obstacle Avoidance Using a Stochastic Reachable Set Based Potential Field. WAFR 2014: 73-89 - [i3]Kendra Lesser, Meeko M. K. Oishi:
Approximate Verification of Partially Observable Discrete Time Stochastic Hybrid Systems. CoRR abs/1410.8054 (2014) - 2013
- [j5]John N. Maidens, Shahab Kaynama, Ian M. Mitchell, Meeko M. K. Oishi, Guy Albert Dumont:
Lagrangian methods for approximating the viability kernel in high-dimensional systems. Autom. 49(7): 2017-2029 (2013) - [j4]Shahab Kaynama, Meeko Oishi:
A Modified Riccati Transformation for Decentralized Computation of the Viability Kernel Under LTI Dynamics. IEEE Trans. Autom. Control. 58(11): 2878-2892 (2013) - [c19]Kendra Lesser, Meeko M. K. Oishi, Richard Scott Erwin:
Stochastic reachability for control of spacecraft relative motion. CDC 2013: 4705-4712 - [i2]Shahab Kaynama, Meeko Oishi:
A Modified Riccati Transformation for Decentralized Computation of the Viability Kernel Under LTI Dynamics. CoRR abs/1302.5990 (2013) - [i1]Shahab Kaynama, Ian M. Mitchell, Meeko Oishi, Guy Albert Dumont:
Scalable Safety-Preserving Robust Control Synthesis for Continuous-Time Linear Systems. CoRR abs/1312.3399 (2013) - 2012
- [c18]Ian M. Mitchell, Mo Chen, Meeko Oishi:
Ensuring Safety of Nonlinear Sampled Data Systems through Reachability1.