ASL LabStanford University
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Prof. Marco Pavone

Prof. Marco Pavone

Faculty

Associate Professor, Department of Aeronautics and Astronautics

Director, Autonomous Systems Laboratory

Director, Center for Automotive Research at Stanford (CARS)

Associate Professor (by courtesy), Information Systems Laboratory

Associate Professor (by courtesy), Computer Science

Associate Professor (by courtesy), Institute for Computational and Mathematical Engineering (ICME)

Ph.D. Massachusetts Institute of Technology, 2010

Publications

355 publications · full lab bibliography

2026
  1. L. Schroth, D. Morton, A. Lahr, D. Gammelli, A. Carron, and M. Pavone, “Multi-Timescale Model Predictive Control for Slow-Fast Systems,” European Control Conference, 2026. (Submitted)
  2. M. Foutter, M. Cercola, L. Wild, Y. Wang, M. Li, D. Gammelli, and M. Pavone, “Do Vision-Language-Action Models Mean What They Say? On the Role of Faithfulness in Embodied Reasoning,” 2026. (Submitted)
  3. Y. Takubo, D. Gammelli, M. Pavone, and S. D'Amico, “Agile Tradespace Exploration for Space Rendezvous Mission Design via Transformers,” IEEE Aerospace Conference, 2026.
  4. J. Dao, M. Ganai, Y. Abukhadra, A. Sridhar, M. Nasr Azadani, K. Luo, C. Barrett, J. Wu, C. Finn, and M. Pavone, “DIRECT: When and Where Should You Allocate Test-Time Compute in Embodied Planners?,” 2026. (Submitted)
  5. R. Römer, J. Balletshofer, J. Thumm, M. Pavone, A. P. Schoellig, and M. Althoff, “From Demonstrations to Safe Deployment: Path-Consistent Safety Filtering for Diffusion Policies,” Proc. IEEE Conf. on Robotics and Automation, 2026. (Submitted)
  6. L. Tresca, C. Schmidt, J. Harrison, F. Rodrigues, G. Zardini, D. Gammelli, and M. Pavone, “Robo-taxi Fleet Coordination at Scale via Reinforcement Learning,” IEEE Transactions on Control of Network Systems, 2026. (Submitted)
  7. M. Ganai, K. Luo, J. Frey, C. Barrett, and M. Pavone, “Self-Supervised Bootstrapping of Action-Predictive Embodied Reasoning,” ArXiv 2602.08167, 2026. (Submitted)
  8. Y. Takubo, A. Dwivedi, S. Ramkumar, L. Pabon, D. Gammelli, M. Pavone, and S. D'Amico, “Semantic Trajectory Generation for Goal-Oriented Spacecraft Rendezvous,” AIAA Scitech Forum, 2026.
2025
  1. L. Li, Z. Fan, W. Cong, X. Liu, Y. Yin, M. Foutter, P. Pan, C. You, Y. Wang, Z. Wang, Y. Zhao, M. Pavone, and Y. Wei, “Martian World Model: Controllable Video Synthesis with Physically Accurate 3D Reconstructions,” Conf. on Neural Information Processing Systems, 2025.
  2. H. Buurmeijer, L. Pabon, J. Alora, R. Kaudinya, G. Haller, and M. Pavone, “Taming High-Dimensional Dynamics: Learning Optimal Projections onto Spectral Submanifolds,” Proc. IEEE Conf. on Decision and Control, 2025. (In Press)
  3. M. Ganai, R. Sinha, C. Agia, D. Morton, L. Di Lillo, and M. Pavone, “Real-Time Out-of-Distribution Failure Prevention via Multi-Modal Reasoning,” Conf. on Robot Learning, 2025. (In Press)
  4. J. Kwok, C. Agia, R. Sinha, M. Foutter, S. Li, I. Stoica, A. Mirhoseini, and M. Pavone, “RoboMonkey: Scaling Test-Time Sampling and Verification for Vision-Language-Action Models,” Conf. on Robot Learning, 2025. (In Press)
  5. C. Agia, R. Sinha, J. Yang, R. Antonova, M. Pavone, H. Nishimura, M. Itkina, and J. Bohg, “CUPID: Curating Data your Robot Loves with Influence Functions,” Conf. on Robot Learning, 2025. (In Press)
  6. D. Berriaud, E. Elokda, D. Jalota, E. Frazzoli, M. Pavone, and F. Dorfler, “To Spend or to Gain: Online Learning in Repeated Karma Auctions,” Proc. Int. Conf. on Autonomous Agents and Multiagent Systems, 2025. (In Press)
  7. D. Morton, R. Antonova, B. Coltin, M. Pavone, and J. Bohg, “Deformable Cargo Transport in Microgravity with Astrobee,” Robotics: Science and Systems - Space Robotics Workshop, 2025.
  8. J. Alora, M. Cenedese, G. Haller, and M. Pavone, “Discovering Dominant Dynamics for Nonlinear Continuum Robot Control,” npj Robotics, 2025.
  9. D. Celestini, A. Afsharrad, D. Gammelli, T. Guffanti, G. Zardini, S. Lall, E. Capelli, S. D'Amico, and M. Pavone, “Generalizable Spacecraft Trajectory Generation via Multimodal Learning with Transformers,” American Control Conference, 2025.
  10. L. Martin, S. Minner, M. Pavone, and M. Schiffer, “It’s All in the Mix: Technology choice between driverless and human-driven vehicles in sharing systems,” European Journal of Operational Research, vol. 324, no. 3, pp. 969-980, 2025.
  11. D. Jalota, M. Ostrovsky, and M. Pavone, “Matching with Transfers under Distributional Constraints,” Games and Economic Behavior, vol. 152, pp. 313--332, 2025.
  12. C. Schmidt, D. Gammelli, J. Harrison, M. Pavone, and F. Rodrigues, “Offline Hierarchical Reinforcement Learning via Inverse Optimization,” Int. Conf. on Learning Representations, 2025.
  13. J. Luke, M. Ribeiro, S. Martin, E. Balogun, G. Cezar, M. Pavone, and R. Rajagopal, “Optimal Coordination of Electric Buses and Battery Storage for Achieving a 24/7 Carbon-Free Electrified Fleet,” Applied Energy, vol. 377, no. 124506, 2025.
  14. F. Marchiori, R. Sinha, C. Agia, A. Robey, G. J. Pappas, M. Conti, and M. Pavone, “Preventing Robotic Jailbreaking via Multimodal Domain Adaptation,” Proc. IEEE Conf. on Robotics and Automation, 2025. (Submitted)
  15. R. Dyro, M. Foutter, R. Li, L. Di Lillo, E. Schmerling, X. Zhou, and M. Pavone, “Realistic Extreme Behavior Generation for Improved AV Testing,” Proc. IEEE Conf. on Robotics and Automation, 2025.
  16. X. Li, M. Alharbi, D. Gammelli, J. Harrison, F. Rodrigues, M. Schiffer, M. Pavone, E. Frazzoli, J. Zhao, and G. Zardini, “Reproducibility in the Control of Autonomous Mobility-on-Demand Systems,” IEEE Transactions on Robotics, 2025. (Submitted)
  17. D. Morton and M. Pavone, “Safe, Task-Consistent Manipulation with Operational Space Control Barrier Functions,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, pp. 187-194, 2025.
  18. A. Elhafsi, D. Morton, and M. Pavone, “Scan, Materialize, Simulate: A Generalizable Framework for Physically Grounded Robot Planning,” ArXiv 2505.14938, 2025. (Submitted)
  19. Y. Kuang, H. Geng, A. Elhafsi, T. Do, P. Abbeel, J. Malik, M. Pavone, and Y. Wang, “SkillBlender: Towards Versatile Humanoid Whole-Body Loco-Manipulation via Skill Blending,” CoRL 2024 Workshop on Whole-body Control and Bimanual Manipulation, 2025.
  20. M. Foutter, D. Gammelli, J. Kruger, E. Foss, P. Bhoj, T. Guffanti, S. D'Amico, and M. Pavone, “Space-LLaVA: a Vision-Language Model Adapted to Extraterrestrial Applications,” IEEE Aerospace Conference, 2025.
  21. Y. Takubo, T. Guffanti, D. Gammelli, M. Pavone, and S. D'Amico, “Towards Robust Spacecraft Trajectory Optimization via Transformers,” IEEE Aerospace Conference, 2025.
  22. M. P. Ronecker, M. Foutter, A. Elhafsi, D. Gammelli, I. Barakaiev, M. Pavone, and D. Watzenig, “Vision Foundation Model Embedding-based Semantic Anomaly Detection,” Proc. IEEE Conf. on Robotics and Automation: Workshop Safe-VLM, 2025.
2024
  1. J. Thumm, C. Agia, M. Pavone, and M. Althoff, “Text2Interaction: Establishing Safe and Preferable Human-Robot Interaction,” Conf. on Robot Learning, 2024. (In Press)
  2. C. Agia, R. Sinha, J. Yang, Z. Cao, R. Antonova, M. Pavone, and J. Bohg, “Unpacking Failure Modes of Generative Policies: Runtime Monitoring of Consistency and Progress,” Conf. on Robot Learning, 2024. (In Press)
  3. L. Roveda and M. Pavone, “Gradient Descent-Based Task-Orientation Robot Control Enhanced With Gaussian Process Predictions,” IEEE Robotics and Automation Letters, vol. 9, no. 9, pp. 8035--8042, 2024.
  4. T. Lew, R. Bonalli, L. Janson, and M. Pavone, “Estimating the convex hull of the image of a set with smooth boundary: error bounds and applications,” Discrete & Computational Geometry, pp. 1--39, 2024.
  5. M. Bazzi, A. Shahid, C. Agia, J. Alora, M. Forgione, D. Piga, F. Braghin, M. Pavone, and L. Roveda, “RoboMorph: In-Context Meta-Learning for Robot Dynamics Modeling,” Proc. of the IFAC/AAAI Int. Conf. on Informatics in Control, Automation and Robotics, 2024.
  6. T. Salzmann, J. Arrizabalaga, J. Andersson, M. Pavone, and M. Ryll, “Learning for CasADi: Data-driven Models in Numerical Optimization,” Learning for Dynamics & Control Conference, 2024.
  7. R. Sinha, A. Elhafsi, C. Agia, M. Foutter, E. Schmerling, and M. Pavone, “Real-Time Anomaly Detection and Planning with Large Language Models,” Robotics: Science and Systems, 2024.
  8. R. A. Brown, D. E. Bernal Neira, D. Venturelli, and M. Pavone, “A Copositive Framework for Analysis of Hybrid Ising-Classical Algorithms,” SIAM Journal on Optimization, vol. 34, no. 2, pp. 1455--1489, 2024.
  9. J. Di, S. Cuevas-Quinones, S. Newdick, T. G. Chen, M. Pavone, M. G. A. Lapôtre, and M. Cutkosky, “Martian Exploration of Lava Tubes (MELT) with ReachBot: Scientific Investigation and Concept of Operations,” Int. Conf. on Space Robotics, 2024.
  10. A. Singhal, D. Gammelli, J. Luke, K. Gopalakrishnan, D. Helmreich, and M. Pavone, “Real-time Control of Electric Autonomous Mobility-on-Demand Systems via Graph Reinforcement Learning,” European Control Conference, 2024.
  11. C. Agia, G. C. Vila, S. Bandyopadhyay, D. S. Bayard, K. Cheung, C. H. Lee, E. Wood, I. Aenishanslin, S. Ardito, L. Fesq, M. Pavone, and I. A. D. Nesnas, “Modeling Considerations for Developing Deep Space Autonomous Spacecraft and Simulators,” IEEE Aerospace Conference, 2024.
  12. R. A. Brown, D. Venturelli, M. Pavone, and D. E. Bernal Neira, “Accelerating Continuous Variable Coherent Ising Machines via Momentum,” Int. Conf. on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 2024.
  13. D. E. B. Neira, R. Brown, P. Sathe, F. Wudarski, M. Pavone, E. G. Rieffel, and D. Venturelli, “Benchmarking the Operation of Quantum Heuristics and Ising Machines: Scoring Parameter Setting Strategies on Optimization Applications,” 2024. (Submitted)
  14. D. Jalota, M. Tsao, and M. Pavone, “Catch Me If You Can: Combatting Fraud in Artificial Currency Based Government Benefits Programs,” 2024. (Submitted)
  15. S. Banerjee, B. Balaban, M. Shirley, K. Bradner, and M. Pavone, “Contingency Planning Using Bi-level Markov Decision Processes for Space Missions,” IEEE Aerospace Conference, 2024.
  16. T. Lew, R. Bonalli, and M. Pavone, “Convex Hulls of Reachable Sets,” IEEE Transactions on Automatic Control, 2024. (Submitted)
  17. C. Chiu, D. Jalota, and M. Pavone, “Credit vs. Discount-Based Congestion Pricing: A Comparison Study,” Proc. IEEE Conf. on Decision and Control, 2024. (In Press)
  18. L. F. Valenzuela, R. Brown, and M. Pavone, “Decentralized Implicit Differentiation,” IEEE Transactions on Control of Network Systems, 2024. (Submitted)
  19. A. Hindy, R. Luo, S. Banerjee, J. Kuck, E. Schmerling, and M. Pavone, “Diagnostic Runtime Monitoring with Martingales,” 2024. (Submitted)
  20. C. Conte, D. Accardo, K. Gopalakrishnan, and M. Pavone, “Evaluating a Reinforcement Learning Approach for Collision Avoidance with Heterogeneous Aircraft,” AIAA SCITECH 2024 Forum, pp. 1860, 2024.
  21. A. Degleris, L. F. Valenzuela, R. Rajagopal, M. Pavone, and A. E. Gamal, “Fast Grid Emissions Sensitivities using Parallel Decentralized Implicit Differentiation,” 2024. (Submitted)
  22. T. G. Chen, S. Newdick, J. Di, C. Bosio, N. Ongole, M. Lapôtre, M. Pavone, and M. R. Cutkosky, “Locomotion as manipulation with ReachBot,” Science Robotics, vol. 9, no. 89, pp. eadi9762, 2024.
  23. R. Bigazzi, L. Baraldi, S. Kousik, R. Cucchiara, and M. Pavone, “Mapping High-level Semantic Regions in Indoor Environments without Object Recognition,” Proc. IEEE Conf. on Robotics and Automation, 2024.
  24. N. Lanzetti, M. Schiffer, M. Ostrovsky, and M. Pavone, “On the Interplay Between Self-Driving Cars and Public Transportation,” IEEE Transactions on Control of Network Systems, vol. 11, no. 3, pp. 1478-1490, 2024.
  25. R. Luo, R. Sinha, Y. Sun, A. Hindy, S. Zhao, S. Savarese, E. Schmerling, and M. Pavone, “Online Distribution Shift Detection via Recency Prediction,” Proc. IEEE Conf. on Robotics and Automation, 2024.
  26. L. Pabon, J. Köhler, J. Alora, P. Eberhard, A. Carron, M. Zeilinger, and M. Pavone, “Perfecting Periodic Trajectory Tracking: Model Predictive Control with a Periodic Observer,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2024.
  27. T. Lew, R. Bonalli, and M. Pavone, “Sample Average Approximation for Stochastic Programming with Equality Constraints,” SIAM Journal on Optimization, vol. 34, no. 4, pp. 3506--3533, 2024.
  28. I. W. Wang, R. Brown, T. L. Patti, A. Anandkumar, M. Pavone, and S. F. Yelin, “Sum-of-Squares inspired Quantum Metaheuristic for Polynomial Optimization with the Hadamard Test and Approximate Amplitude Constraints,” 2024. (Submitted)
  29. D. Morton, M. Cutkosky, and M. Pavone, “Task-Driven Manipulation with Reconfigurable Parallel Robots,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2024.
  30. S. Jorgensen and M. Pavone, “The Matroid Team Servicing Orienteers Problem and its Variants: Constrained Routing of Heterogeneous Teams with Risky Traversal,” Int. Journal of Robotics Research, vol. 43, no. 1, pp. 34--52, 2024.
  31. D. Celestini, D. Gammelli, T. Guffanti, S. D'Amico, E. Capelli, and M. Pavone, “Transformer-based Model Predictive Control: Trajectory Optimization via Sequence Modeling,” IEEE Robotics and Automation Letters, vol. 9, no. 11, pp. 9280--9827, 2024.
  32. T. Guffanti, D. Gammelli, S. D'Amico, and M. Pavone, “Transformers for Trajectory Optimization with Application to Spacecraft Rendezvous,” IEEE Aerospace Conference, 2024.
  33. D. Jalota, M. Ostrovsky, and M. Pavone, “When Simple is Near-Optimal in Security Games,” 2024. (Submitted)
  34. L. Paparusso, S. Kousik, E. Schmerling, F. Braghin, and M. Pavone, “ZAPP! Zonotope Agreement of Prediction and Planning for Continuous-Time Collision Avoidance with Discrete-Time Dynamics,” Proc. IEEE Conf. on Robotics and Automation, 2024. (Submitted)
2023
  1. M. Ribeiro, J. Luke, S. Martin, E. Balogun, G. Cezar, M. Pavone, and R. Rajagopal, “Towards a 24/7 Carbon-Free Electric Fleet: A Digital Twin Framework,” Energy Proceedings, 2023.
  2. M. Foutter, R. Sinha, S. Banerjee, and M. Pavone, “Self-Supervised Model Generalization using Out-of-Distribution Detection,” Conf. on Robot Learning - Workshop on Out-of-Distribution Generalization in Robotics, 2023.
  3. K. Lin, C. Agia, T. Migimatsu, M. Pavone, and J. Bohg, “Text2Motion: From Natural Language Instructions to Feasible Plans,” Autonomous Robots, vol. 47, no. 8, pp. 1345–-1365, 2023.
  4. A. Elhafsi, R. Sinha, C. Agia, E. Schmerling, I. A. D. Nesnas, and M. Pavone, “Semantic Anomaly Detection with Large Language Models,” Autonomous Robots, vol. 47, no. 8, pp. 1035--1055, 2023.
  5. D. Jalota, K. Solovey, K. Gopalakrishnan, S. Zoepf, H. Balakrishnan, and M. Pavone, “When Efficiency meets Equity in Congestion Pricing and Revenue Refunding Schemes,” IEEE Transactions on Control of Network Systems, 2023. (In Press)
  6. D. Gammelli, J. Harrison, K. Yang, M. Pavone, F. Rodrigues, and F. C. Pereira, “Graph Reinforcement Learning for Network Control via Bi-Level Optimization,” Int. Conf. on Machine Learning, 2023.
  7. S. M. Richards, J. J. Slotine, N. Azizan, and M. Pavone, “Learning Control-Oriented Dynamical Structure from Data,” Int. Conf. on Machine Learning, 2023. (In Press)
  8. J. Alora, M. Cenedese, E. Schmerling, G. Haller, and M. Pavone, “Practical Deployment of Spectral Submanifold Reduction for Optimal Control of High-Dimensional Systems,” IFAC World Congress, 2023.
  9. S. Newdick, N. Ongole, T. G. Chen, E. Schmerling, M. R. Cutkosky, and M. Pavone, “Motion Planning for a Climbing Robot with Stochastic Grasps,” Proc. IEEE Conf. on Robotics and Automation, 2023.
  10. S. Banerjee, A. Sharma, E. Schmerling, M. Spolaor, M. Nemerouf, and M. Pavone, “Data Lifecycle Management in Evolving Input Distributions for Learning-based Aerospace Applications,” IEEE Aerospace Conference, 2023.
  11. S. Newdick, T. G. Chen, B. Hockman, E. Schmerling, M. R. Cutkosky, and M. Pavone, “Designing ReachBot: System Design Process with a Case Study of a Martian Lava Tube Mission,” IEEE Aerospace Conference, 2023.
  12. R. Bonalli, T. Lew, and M. Pavone, “Analysis of Theoretical and Numerical Properties of Sequential Convex Programming for Continuous-Time Optimal Control,” IEEE Transactions on Automatic Control, vol. 68, no. 8, pp. 4570--4585, 2023.
  13. K. Leung, N. Aréchiga, and M. Pavone, “Backpropagation through signal temporal logic specifications: Infusing logical structure into gradient-based methods,” Int. Journal of Robotics Research, vol. 42, no. 6, pp. 356--370, 2023.
  14. D. Jalota, K. Solovey, M. Tsao, S. Zoepf, and M. Pavone, “Balancing Fairness and Efficiency in Traffic Routing via Interpolated Traffic Assignment,” Autonomous Agents and Multi-Agent Systems, vol. 37, no. 32, pp. 1--40, 2023.
  15. R. Sinha, E. Schmerling, and M. Pavone, “Closing the Loop on Runtime Monitors with Fallback-Safe MPC,” Proc. IEEE Conf. on Decision and Control, 2023.
  16. M. Nakanoya, S. S. Narasimhan, S. Bhat, A. Anemogiannis, A. Datta, S. Katti, S. Chinchali, and M. Pavone, “Co-Design of Communication and Machine Inference for Cloud Robotics,” Autonomous Robots, vol. 47, pp. 579–-594, 2023.
  17. S. M. Richards, N. Azizan, J. J. Slotine, and M. Pavone, “Control-Oriented Meta-Learning,” Int. Journal of Robotics Research, vol. 42, no. 10, pp. 777--797, 2023.
  18. D. Jalota, J. Lazarus, A. Bayen, and M. Pavone, “Credit-Based Congestion Pricing: Equilibrium Properties and Optimal Scheme Design,” Proc. IEEE Conf. on Decision and Control, 2023.
  19. J. Alora, M. Cenedese, E. Schmerling, G. Haller, and M. Pavone, “Data-Driven Spectral Submanifold Reduction for Nonlinear Optimal Control of High-Dimensional Robots,” Proc. IEEE Conf. on Robotics and Automation, 2023.
  20. M. Tsao, K. Gopalakrishnan, K. Yang, and M. Pavone, “Differentially Private Stochastic Convex Optimization for Network Routing Applications,” Proc. IEEE Conf. on Decision and Control, 2023.
  21. L. F. Valenzuela, A. Degleris, A. E. Gamal, M. Pavone, and R. Rajagopal, “Dynamic Locational Marginal Emissions via Implicit Differentiation,” IEEE Transactions on Power Systems, vol. 39, no. 1, pp. 1138--1147, 2023.
  22. T. Lew, R. Bonalli, and M. Pavone, “Exact Characterization of the Convex Hulls of Reachable Sets,” Proc. IEEE Conf. on Decision and Control, 2023.
  23. D. Jalota, M. Pavone, Q. Qi, and Y. Ye, “Fisher Markets with Linear Constraints: Equilibrium Properties and Efficient Distributed Algorithms,” Games and Economic Behavior, vol. 141, pp. 223--260, 2023.
  24. T. Enders, J. Harrison, M. Pavone, and M. Schiffer, “Hybrid Multi-agent Deep Reinforcement Learning for Autonomous Mobility on Demand Systems,” 2023.
  25. A. Bourdillon, A. Garg, H. Wang, Y. Woo, M. Pavone, and J. Boyd, “Integration of Reinforcement Learning in a Virtual Robotic Surgical Simulation,” Journal of Surgical Innovations, vol. 30, no. 1, pp. 94--102, 2023.
  26. D. Dayan, K. Solovey, M. Pavone, and D. Halperin, “Near-Optimal Multi-Robot Motion Planning with Finite Sampling,” IEEE Transactions on Robotics, vol. 39, no. 5, pp. 3422--3436, 2023.
  27. D. Jalota, K. Gopalakrishnan, N. Azizan, R. Johari, and M. Pavone, “Online Learning for Traffic Routing under Unknown Preferences,” Int. Conf. on Artificial Intelligence and Statistics, 2023.
  28. D. Jalota, D. Paccagnan, M. Schiffer, and M. Pavone, “Online Routing Over Parallel Networks: Deterministic Limits and Data-driven Enhancements,” INFORMS Journal on Computing, vol. 35, no. 3, pp. 560--577, 2023.
  29. M. Tsao, K. Gopalakrishnan, K. Yang, and M. Pavone, “Privacy-Aware Control of Cyber Physical Systems,” Smarter Cyber Physical Systems: Enabling Methodologies and Application, 2023. (Submitted)
  30. M. Tsao, K. Gopalakrishnan, K. Yang, and M. Pavone, “Privacy-Aware Control of Cyber Physical Systems,” Smarter Cyber Physical Systems: Enabling Methodologies and Application, 2023. (Submitted)
  31. T. Salzmann, E. Kaufmann, J. Arrizabalaga, M. Pavone, D. Scaramuzza, and M. Ryll, “Real-Time Neural MPC: Deep Learning Model Predictive Control for Quadrotors and Agile Robotic Platforms,” IEEE Robotics and Automation Letters, vol. 8, no. 4, pp. 2397--2404, 2023.
  32. T. Lew, R. Bonalli, and M. Pavone, “Risk-Averse Trajectory Optimization via Sample Average Approximation,” IEEE Robotics and Automation Letters, vol. 9, no. 2, pp. 1500--1507, 2023.
  33. S. Singh, B. Landry, A. Majumdar, J. J. E. Slotine, and M. Pavone, “Robust Feedback Motion Planning via Contraction Theory,” Int. Journal of Robotics Research, vol. 42, no. 9, pp. 655--688, 2023.
  34. J. Alora, L. Pabon, J. Köhler, M. Cenedese, E. Schmerling, Z. M. N., G. Haller, and M. Pavone, “Robust Nonlinear Reduced-Order Model Predictive Control,” Proc. IEEE Conf. on Decision and Control, 2023.
  35. R. Luo, S. Zhao, J. Kuck, B. Ivanovic, S. Savarese, E. Schmerling, and M. Pavone, “Sample-Efficient Safety Assurances using Conformal Prediction,” Int. Journal of Robotics Research, 2023.
2022
  1. M. Tsao, K. Yang, K. Gopalakrishnan, and M. Pavone, “Private Location Sharing for Decentralized Routing Services,” Proc. IEEE Int. Conf. on Intelligent Transportation Systems, 2022.
  2. B. Ivanovic, K. H. Lee, P. Tokmakov, B. Wulfe, R. McAllister, A. Gaidon, and M. Pavone, “Heterogeneous-Agent Trajectory Forecasting Incorporating Class Uncertainty,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2022.
  3. B. Ivanovic, Y. Lin, S. Shrivastava, P. Chakravarty, and M. Pavone, “Propagating State Uncertainty Through Trajectory Forecasting,” Proc. IEEE Conf. on Robotics and Automation, 2022.
  4. A. Wu, T. Lew, K. Solovey, E. Schmerling, and M. Pavone, “Robust-RRT: Probabilistically-Complete Motion Planning for Uncertain Nonlinear Systems,” Int. Symp. on Robotics Research, 2022.
  5. R. Luo, S. Zhao, J. Kuck, B. Ivanovic, S. Savarese, E. Schmerling, and M. Pavone, “Sample-Efficient Safety Assurances using Conformal Prediction,” Workshop on Algorithmic Foundations of Robotics, 2022.
  6. T. Lew, L. Janson, R. Bonalli, and M. Pavone, “A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis,” Learning for Dynamics & Control Conference, 2022.
  7. A. J. Thorpe, T. Lew, M. M. K. Oishi, and M. Pavone, “Data-Driven Chance Constrained Control using Kernel Distribution Embeddings,” Learning for Dynamics & Control Conference, 2022.
  8. S. Schneider, A. Bylard, T. G. Chen, P. Wang, M. R. Cutkosky, and M. Pavone, “ReachBot: A Small Robot for Large Mobile Manipulation Tasks,” IEEE Aerospace Conference, 2022.
  9. D. Malyuta, T. P. Reynolds, M. Szmuk, T. Lew, R. Bonalli, M. Pavone, and B. Acikmese, “Convex Optimization for Trajectory Generation,” IEEE Control Systems Magazine, vol. 42, no. 5, pp. 40--113, 2022.
  10. A. McClellan, J. Lorenzetti, M. Pavone, and C. Farhat, “A Physics-Based Digital Twin for Model Predictive Control of Autonomous Unmanned Aerial Vehicle Landing,” Philosophical Transactions of the Royal Society A, vol. 380, 2022.
  11. R. Sinha, S. Sharma, S. Banerjee, T. Lew, R. Luo, S. M. Richards, Y. Sun, E. Schmerling, and M. Pavone, “A System-Level View on Out-of-Distribution Data in Robotics,” 2022.
  12. R. Brown, E. Schmerling, N. Azizan, and M. Pavone, “A Unified View of SDP-based Neural Network Verification through Completely Positive Programming,” Int. Conf. on Artificial Intelligence and Statistics, 2022.
  13. R. Sinha, J. Harrison, S. M. Richards, and M. Pavone, “Adaptive Robust Model Predictive Control via Uncertainty Cancellation,” IEEE Transactions on Automatic Control, 2022. (In Press)
  14. R. Sinha, J. Harrison, S. M. Richards, and M. Pavone, “Adaptive Robust Model Predictive Control with Matched and Unmatched Uncertainty,” American Control Conference, 2022.
  15. G. Zardini, N. Lanzetti, M. Pavone, and E. Frazzoli, “Analysis and Control of Autonomous Mobility-on-Demand Systems: A Review,” Annual Review of Control, Robotics, and Autonomous Systems, vol. 5, no. 1, pp. 633--658, 2022.
  16. D. Jalota, K. Solovey, M. Tsao, S. Zoepf, and M. Pavone, “Balancing Fairness and Efficiency in Traffic Routing via Interpolated Traffic Assignment,” Proc. Int. Conf. on Autonomous Agents and Multiagent Systems, 2022.
  17. J. Willes, J. Harrison, A. Harakeh, C. Finn, M. Pavone, and S. Waslander, “Bayesian Embeddings for Few-Shot Open World Recognition,” IEEE Transactions on Pattern Analysis & Machine Intelligence, 2022.
  18. G. Zardini, N. Lanzetti, A. Censi, E. Frazzoli, and M. Pavone, “Co-Design to Enable User-Friendly Tools to Assess the Impact of Future Mobility Solutions,” IEEE Transactions on Network Science and Engineering, 2022. (In Press)
  19. A. Cauligi, P. Culbertson, E. Schmerling, M. Schwager, B. Stellato, and M. Pavone, “CoCo: Online Mixed-Integer Control via Supervised Learning,” IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 1447--1454, 2022.
  20. D. Gammelli, K. Yang, J. Harrison, F. Rodrigues, F. Pereira, and M. Pavone, “Graph Meta-Reinforcement Learning for Transferable Autonomous Mobility-on-Demand,” ACM Int. Conf. on Knowledge Discovery and Data Mining, 2022.
  21. D. Gammelli, J. Harrison, K. Yang, M. Pavone, F. Rodrigues, and P. C. Francisco, “Graph Reinforcement Learning for Network Control via Bi-Level Optimization,” Learning on Graphs Conference, 2022.
  22. J. Lorenzetti, A. McClellan, C. Farhat, and M. Pavone, “Linear Reduced-Order Model Predictive Control,” IEEE Transactions on Automatic Control, vol. 67, no. 11, pp. 5980--5995, 2022.
  23. R. Luo, A. Bhatnagar, H. Wang, C. Xiong, S. Savarese, Y. Bai, S. Zhao, S. Ermon, E. Schmerling, and M. Pavone, “Local Calibration: Metrics and Recalibration,” Proc. Conf. on Uncertainty in Artificial Intelligence, 2022.
  24. T. Salzmann, M. Pavone, and M. Ryll, “Motron: Multimodal Probabilistic Human Motion Forecasting,” IEEE Conf. on Computer Vision and Pattern Recognition, 2022.
  25. M. Pavone, A. Saberi, M. Schiffer, and M. Tsao, “Online Hypergraph Matching with Delays,” Operations Research, vol. 70, no. 4, pp. 2194-2212, 2022.
  26. M. Schiffer, N. Boysen, G. Laporte, and M. Pavone, “Optimal picking policies in e-commerce warehouses,” Management Science, vol. 68, no. 10, pp. 7497-7517, 2022.
  27. M. Pavone, M. Cutkosky, M. Lapôtre, S. Schneider, T. G. Chen, and A. Bylard, “ReachBot: a Small Robot for Large Mobile Manipulation Tasks in Martian Cave Environments,” NASA NIAC Program, 2022.
  28. T. G. Chen, B. Miller, C. Winston, S. Schneider, A. Bylard, M. Pavone, and M. R. Cutkosky, “ReachBot: A Small Robot with Exceptional Reach for Rough Terrain,” Proc. IEEE Conf. on Robotics and Automation, 2022.
  29. S. Wollenstein-Betech, M. Salazar, A. Houshmand, M. Pavone, I. C. Paschalidis, and C. G. Cassandras, “Routing and Rebalancing Intermodal Autonomous Mobility-on-Demand Systems in Mixed Traffic,” IEEE Transactions on Intelligent Transportation Systems, vol. 23, no. 8, pp. 2261--2276, 2022.
  30. T. Lew, A. Sharma, J. Harrison, A. Bylard, and M. Pavone, “Safe Active Dynamics Learning and Control: A Sequential Exploration-Exploitation Framework,” IEEE Transactions on Robotics, vol. 38, no. 5, pp. 2888--2907, 2022.
  31. M. Selim, A. Alanwar, S. Kousik, G. Gao, M. Pavone, and K. Johansson, “Safe Reinforcement Learning Using Black-Box Reachability Analysis,” IEEE Robotics and Automation Letters, vol. 7, no. 4, pp. 10665-10672, 2022.
  32. R. Dyro, E. Schmerling, N. Arechiga, and M. Pavone, “Second-Order Sensitivity Analysis for Bilevel Optimization,” Int. Conf. on Artificial Intelligence and Statistics, 2022.
  33. K. Leung and M. Pavone, “Semi-Supervised Trajectory-Feedback Controller Synthesis with Signal Temporal Logic Specifications,” American Control Conference, 2022.
  34. R. Bonalli, T. Lew, and M. Pavone, “Sequential Convex Programming For Non-Linear Stochastic Optimal Control,” ESAIM: Control, Optimisation & Calculus of Variations, vol. 28, 2022.
  35. T. G. Chen, A. Cauligi, S. A. Suresh, M. Pavone, and M. R. Cutkosky, “Testing Gecko-Inspired Adhesives with Astrobee Aboard the ISS,” IEEE Robotics and Automation Magazine, vol. 29, no. 3, pp. 24--33, 2022.
  36. M. Tsao, K. Yang, S. Zoepf, and M. Pavone, “Trust but Verify: Cryptographic Data Privacy for Mobility Management,” IEEE Transactions on Control of Network Systems, vol. 9, no. 1, pp. 50--61, 2022.
  37. P. Zhao, A. Lakshmanan, K. Ackerman, A. Gahlawat, M. Pavone, and N. Hovakimyan, “Tube-Certified Trajectory Tracking for Nonlinear Systems With Robust Control Contraction Metrics,” IEEE Robotics and Automation Letters, vol. 7, no. 2, pp. 5528-5535, 2022.
  38. F. Mahlknecht, J. Alora, S. Jain, E. Schmerling, R. Bonalli, G. Haller, and M. Pavone, “Using Spectral Submanifolds for Nonlinear Periodic Control,” Proc. IEEE Conf. on Decision and Control, 2022.
2021
  1. J. Cheng, M. Pavone, S. Katti, S. Chinchali, and A. Tang, “Data Sharing and Compression for Cooperative Networked Control,” Conf. on Neural Information Processing Systems, 2021.
  2. B. Landry, H. Dai, and M. Pavone, “SEAGuL: Sample Efficient Adversarially Guided Learning of Value Functions,” Learning for Dynamics & Control Conference, 2021.
  3. D. Jalota, K. Solovey, K. Gopalakrishnan, S. Zoepf, H. Balakrishnan, and M. Pavone, “When Efficiency meets Equity in Congestion Pricing and Revenue Refunding Schemes,” ACM Conf. on Equity and Access in Algorithms, Mechanisms, and Optimization, 2021.
  4. J. Luke, M. Salazar, R. Rajagopal, and M. Pavone, “Joint Optimization of Autonomous Electric Vehicle Fleet Operations and Charging Station Siting,” Proc. IEEE Int. Conf. on Intelligent Transportation Systems, 2021.
  5. K. Yang, M. Tsao, X. Xu, and M. Pavone, “Real-Time Control of Mixed Fleets in Mobility-on-Demand Systems,” Proc. IEEE Int. Conf. on Intelligent Transportation Systems, 2021.
  6. J. Schilliger, T. Lew, S. M. Richards, S. Hanggi, M. Pavone, and C. Onder, “Control Barrier Functions for Cyber-Physical Systems and Applications to NMPC,” IEEE Robotics and Automation Letters, vol. 6, no. 4, pp. 8623--8630, 2021.
  7. S. Roelofs, B. Landry, M. K. Jalil, A. Martin, S. Koppaka, S. K. Y. Tang, and M. Pavone, “Vision-based Autonomous Disinfection of High Touch Surfaces in Indoor Environments,” Int. Conf. on Control, Automation and Systems, 2021.
  8. S. M. Richards, N. Azizan, J. J. Slotine, and M. Pavone, “Adaptive-Control-Oriented Meta-Learning for Nonlinear Systems,” Robotics: Science and Systems, 2021.
  9. H. Dai, B. Landry, L. Yang, M. Pavone, and R. Tedrake, “Lyapunov-Stable Neural-Network Control,” Robotics: Science and Systems, 2021.
  10. A. Sharma, N. Azizan, and M. Pavone, “Sketching Curvature for Efficient Out-of-Distribution Detection for Deep Neural Networks,” Proc. Conf. on Uncertainty in Artificial Intelligence, 2021.
  11. M. Nakanoya, S. Chinchali, A. Anemogiannis, A. Datta, S. Katti, and M. Pavone, “Task-relevant Representation Learning for Networked Robotic Perception,” Robotics: Science and Systems, 2021.
  12. A. Bylard, R. Bonalli, and M. Pavone, “Composable Geometric Motion Policies using Multi-Task Pullback Bundle Dynamical Systems,” Proc. IEEE Conf. on Robotics and Automation, 2021.
  13. K. Solovey, S. Bandyopadhyay, F. Rossi, M. T. Wolf, and M. Pavone, “Fast Near-Optimal Heterogeneous Task Allocation via Flow Decomposition,” Proc. IEEE Conf. on Robotics and Automation, 2021.
  14. S. Schaefer, K. Leung, B. Ivanovic, and M. Pavone, “Leveraging Neural Network Gradients within Trajectory Optimization for Proactive Human-Robot Interactions,” Proc. IEEE Conf. on Robotics and Automation, 2021.
  15. S. Tonkens, J. Lorenzetti, and M. Pavone, “Soft Robot Optimal Control Via Reduced Order Finite Element Models,” Proc. IEEE Conf. on Robotics and Automation, 2021.
  16. B. Ivanovic, K. Leung, E. Schmerling, and M. Pavone, “Multimodal Deep Generative Models for Trajectory Prediction: A Conditional Variational Autoencoder Approach,” IEEE Robotics and Automation Letters, vol. 6, no. 2, pp. 295--302, 2021.
  17. D. Gammelli, K. Yang, J. Harrison, F. Rodrigues, F. C. Pereira, and M. Pavone, “Graph Neural Network Reinforcement Learning for Autonomous Mobility-on-Demand Systems,” Proc. IEEE Conf. on Decision and Control, 2021.
  18. S. Singh, S. M. Richards, V. Sindhwani, J. J. E. Slotine, and M. Pavone, “Learning Stabilizable Nonlinear Dynamics with Contraction-Based Regularization,” Int. Journal of Robotics Research, vol. 40, no. 10--11, pp. 1123-1150, 2021.
  19. R. A. Brown, F. Rossi, K. Solovey, M. Tsao, M. T. Wolf, and M. Pavone, “On Local Computation for Network-Structured Convex Optimization in Multi-Agent Systems,” IEEE Transactions on Control of Network Systems, vol. 8, no. 2, pp. 542-554, 2021.
  20. A. Estandia, M. Schiffer, F. Rossi, J. Luke, E. C. Kara, R. Rajagopal, and M. Pavone, “On the Interaction between Autonomous Mobility on Demand Systems and Power Distribution Networks -- An Optimal Power Flow Approach,” IEEE Transactions on Control of Network Systems, vol. 8, no. 3, pp. 1163--1176, 2021.
  21. N. Lanzetti, M. Schiffer, M. Ostrovsky, and M. Pavone, “On the Interplay Between Self-Driving Cars and Public Transportation: A Game-theoretic Perspective,” Proceedings of the TSL Second Triennial Conference, 2021.
  22. R. Dyro, J. Harrison, A. Sharma, and M. Pavone, “Particle MPC for Uncertain and Learning-Based Control,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2021.
  23. M. P. Chapman, R. Bonalli, K. M. Smith, I. Yang, M. Pavone, and C. J. Tomlin, “Risk-sensitive safety analysis using Conditional Value-at-Risk,” IEEE Transactions on Automatic Control, vol. 67, no. 12, pp. 6521-6536, 2021.
2020
  1. J. Harrison, A. Sharma, C. Finn, and M. Pavone, “Continuous Meta-Learning without Tasks,” Conf. on Neural Information Processing Systems, 2020.
  2. H. Dai, B. Landry, M. Pavone, and R. Tedrake, “Counter-Example Guided Synthesis of Neural Network Lyapunov Functions for Piecewise Linear Systems,” Proc. IEEE Conf. on Decision and Control, 2020.
  3. J. Lorenzetti and M. Pavone, “Error Bounds for Reduced Order Model Predictive Control,” Proc. IEEE Conf. on Decision and Control, 2020.
  4. M. Itkina, B. Ivanovic, R. Senanayake, M. J. Kochenderfer, and M. Pavone, “Evidential Sparsification of Multimodal Latent Spaces in Conditional Variational Autoencoders,” Conf. on Neural Information Processing Systems, 2020.
  5. D. Jalota, M. Pavone, Q. Qi, and Y. Ye, “Markets for Efficient Public Good Allocation with Social Distancing,” The Conference on Web and Internet Economics (WINE), 2020.
  6. M. Pavone, A. Saberi, M. Schiffer, and M. Tsao, “Online Hypergraph Matching with Delays,” The Conference on Web and Internet Economics (WINE), 2020.
  7. B. Ivanovic, A. Elhafsi, G. Rosman, A. Gaidon, and M. Pavone, “MATS: An Interpretable Trajectory Forecasting Representation for Planning and Control,” Conf. on Robot Learning, 2020.
  8. S. Banerjee, J. Harrison, P. M. Furlong, and M. Pavone, “Adaptive Meta-Learning for Identification of Rover-Terrain Dynamics,” Int. Symp. on Artificial Intelligence, Robotics and Automation in Space, 2020.
  9. A. Cauligi, T. Chen, S. A. Suresh, M. Dille, R. G. Ruiz, A. M. Vargas, M. Pavone, and M. R. Cutkosky, “Design and Development of a Gecko-Adhesive Gripper for the Astrobee Free-Flying Robot,” Int. Symp. on Artificial Intelligence, Robotics and Automation in Space, 2020.
  10. H. Nishimura, B. Ivanovic, A. Gaidon, M. Pavone, and M. Schwager, “Risk-Sensitive Sequential Action Control with Multi-Modal Human Trajectory Forecasting for Safe Crowd-Robot Interaction,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2020.
  11. S. Wollenstein-Betech, A. Houshmand, M. Salazar, M. Pavone, C. G. Cassandras, and I. C. Paschalidis, “Congestion-aware Routing and Rebalancing of Autonomous Mobility-on-Demand Systems in Mixed Traffic,” Proc. IEEE Int. Conf. on Intelligent Transportation Systems, 2020.
  12. G. Zardini, N. Lanzetti, M. Salazar, A. Censi, E. Frazzoli, and M. Pavone, “On the Co-Design of AV-Enabled Mobility Systems,” Proc. IEEE Int. Conf. on Intelligent Transportation Systems, 2020.
  13. T. Lew and M. Pavone, “Sampling-based Reachability Analysis: A Random Set Theory Approach with Adversarial Sampling,” Conf. on Robot Learning, 2020.
  14. T. Salzmann, B. Ivanovic, P. Chakravarty, and M. Pavone, “Trajectron++: Dynamically-Feasible Trajectory Forecasting With Heterogeneous Data,” European Conf. on Computer Vision, 2020.
  15. F. Boewing, M. Schiffer, M. Salazar, and M. Pavone, “A Vehicle Coordination and Charge Scheduling Algorithm for Electric Autonomous Mobility-on-Demand Systems,” American Control Conference, 2020.
  16. A. Elhafsi, B. Ivanovic, L. Janson, and M. Pavone, “Map-Predictive Motion Planning in Unknown Environments,” Proc. IEEE Conf. on Robotics and Automation, 2020.
  17. J. Lorenzetti and M. Pavone, “A Simple and Efficient Tube-based Robust Output Feedback Model Predictive Control Scheme,” European Control Conference, 2020.
  18. T. Lew, R. Bonalli, and M. Pavone, “Chance-Constrained Sequential Convex Programming for Robust Trajectory Optimization,” European Control Conference, 2020.
  19. R. A. Brown, F. Rossi, K. Solovey, M. T. Wolf, and M. Pavone, “Exploiting Locality and Structure for Distributed Optimization in Multi-Agent Systems,” European Control Conference, 2020.
  20. F. J. R. Verbruggen, M. Salazar, M. Pavone, and T. Hofman, “Joint Design and Control of Electric Vehicle Propulsion Systems,” European Control Conference, 2020.
  21. K. Solovey, L. Janson, E. Schmerling, E. Frazzoli, and M. Pavone, “Revisiting the Asymptotic Optimality of RRT*,” Proc. IEEE Conf. on Robotics and Automation, 2020.
  22. M. Tsao, K. Solovey, and M. Pavone, “Sample Complexity of Probabilistic Roadmaps via Epsilon-nets,” Proc. IEEE Conf. on Robotics and Automation, 2020.
  23. A. Cauligi, P. Culbertson, B. Stellato, D. Bertsimas, M. Schwager, and M. Pavone, “Learning Mixed-Integer Convex Optimization Strategies for Robot Planning and Control,” Proc. IEEE Conf. on Decision and Control, 2020.
  24. S. Banerjee, T. Lew, R. Bonalli, A. Alfaadhel, I. A. Alomar, H. M. Shageer, and M. Pavone, “Learning-based Warm-Starting for Fast Sequential Convex Programming and Trajectory Optimization,” IEEE Aerospace Conference, 2020.
  25. S. Chinchali, E. Pergament, M. Nakanoya, E. Cidon, E. Zhang, D. Bharadia, M. Pavone, and S. Katti, “Sampling Training Data for Distributed Learning between Robots and the Cloud,” Int. Symp. on Experimental Robotics, 2020.
  26. A. McClellan, J. Lorenzetti, M. Pavone, and C. Farhat, “Projection-based Model Order Reduction for Flight Dynamics and Model Predictive Control,” AIAA Scitech Forum, 2020.
  27. G. Zardini, N. Lanzetti, M. Salazar, A. Censi, E. Frazzoli, and M. Pavone, “Towards a Co-Design Framework for Future Mobility Systems,” Annual Meeting of the Transportation Research Board, 2020.
  28. J. Lorenzetti, A. McClellan, C. Farhat, and M. Pavone, “UAV Aircraft Carrier Landing Using CFD-Based Model Predictive Control,” AIAA Scitech Forum, 2020.
  29. K. Leung, N. Aréchiga, and M. Pavone, “Back-propagation through signal temporal logic specifications: Infusing logical structure into gradient-based methods,” Workshop on Algorithmic Foundations of Robotics, 2020.
  30. M. Mote, M. Egerstedt, E. Feron, A. Bylard, and M. Pavone, “Collision-Inclusive Trajectory Optimization for Free-Flying Spacecraft,” AIAA Journal of Guidance, Control, and Dynamics, vol. 43, no. 7, pp. 1247-1258, 2020.
  31. X. Wang, K. Leung, and M. Pavone, “Infusing Reachability-Based Safety into Planning and Control for Multi-agent Interactions,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2020.
  32. M. Salazar, N. Lanzetti, F. Rossi, M. Schiffer, and M. Pavone, “Intermodal Autonomous Mobility-on-Demand,” IEEE Transactions on Intelligent Transportation Systems, vol. 21, no. 9, pp. 3946--3960, 2020.
  33. J. DeCastro, K. Leung, N. Aréchiga, and M. Pavone, “Interpretable Policies from Formally-Specified Temporal Properties,” Proc. IEEE Int. Conf. on Intelligent Transportation Systems, 2020.
  34. K. Leung, E. Schmerling, M. Zhang, M. Chen, J. Talbot, J. C. Gerdes, and M. Pavone, “On Infusing Reachability-Based Safety Assurance within Planning Frameworks for Human-Robot Vehicle Interactions,” Int. Journal of Robotics Research, vol. 39, no. 10--11, pp. 1326--1345, 2020.
  35. F. Rossi, R. Iglesias, M. Alizadeh, and M. Pavone, “On the Interaction Between Autonomous Mobility-on-Demand Systems and the Power Network: Models and Coordination Algorithms,” IEEE Transactions on Control of Network Systems, vol. 7, no. 1, pp. 384--397, 2020.
  36. J. Willes, J. Harrison, A. Harakeh, C. Finn, M. Pavone, and S. Waslander, “Open-Set Incremental Learning via Bayesian Prototypical Embeddings,” Conf. on Neural Information Processing Systems - Workshop on Meta-Learning, 2020.
2019
  1. J. Lacotte, M. Pilanci, and M. Pavone, “High-Dimensional Optimization in Adaptive Random Subspaces,” Conf. on Neural Information Processing Systems, 2019.
  2. J. Lacotte, M. Ghavamzadeh, Y. Chow, and M. Pavone, “Risk-Sensitive Generative Adversarial Imitation Learning,” Int. Conf. on Artificial Intelligence and Statistics, 2019.
  3. M. Salazar, M. Tsao, I. Aguiar, M. Schiffer, and M. Pavone, “A Congestion-aware Routing Scheme for Autonomous Mobility-on-Demand Systems,” European Control Conference, 2019.
  4. J. Zgraggen, M. Tsao, M. Salazar, M. Schiffer, and M. Pavone, “A Model Predictive Control Scheme for Intermodal Autonomous Mobility-on-Demand,” Proc. IEEE Int. Conf. on Intelligent Transportation Systems, 2019.
  5. M. Salazar, A. Houshmand, C. G. Cassandras, and M. Pavone, “Optimal Routing and Energy Management Strategies for Plug-in Hybrid Electric Vehicles,” Proc. IEEE Int. Conf. on Intelligent Transportation Systems, 2019.
  6. B. Landry, J. Lorenzetti, Z. Manchester, and M. Pavone, “Bilevel Optimization for Planning through Contact: A Semidirect Method,” Int. Symp. on Robotics Research, 2019.
  7. B. Ivanovic and M. Pavone, “The Trajectron: Probabilistic Multi-Agent Trajectory Modeling with Dynamic Spatiotemporal Graphs,” IEEE Int. Conf. on Computer Vision, 2019.
  8. A. Sharma, J. Harrison, M. Tsao, and M. Pavone, “Robust and Adaptive Planning under Model Uncertainty,” Int. Conf. on Automated Planning and Scheduling, 2019.
  9. B. Landry, Z. Manchester, and M. Pavone, “A Differentiable Augmented Lagrangian Method for Bilevel Nonlinear Optimization,” Robotics: Science and Systems, 2019.
  10. K. Leung, N. Aréchiga, and M. Pavone, “Backpropagation for Parametric STL,” IEEE Intelligent Vehicles Symposium: Workshop on Unsupervised Learning for Automated Driving, 2019.
  11. S. Chinchali, A. Sharma, J. Harrison, A. Elhafsi, D. Kang, E. Pergament, E. Cidon, S. Katti, and M. Pavone, “Network Offloading Policies for Cloud Robotics: a Learning-based Approach,” Robotics: Science and Systems, 2019.
  12. J. Lorenzetti, B. Landry, S. Singh, and M. Pavone, “Reduced Order Model Predictive Control For Setpoint Tracking,” European Control Conference, 2019.
  13. K. Solovey, M. Salazar, and M. Pavone, “Scalable and Congestion-aware Routing for Autonomous Mobility-on-Demand via Frank-Wolfe Optimization,” Robotics: Science and Systems, 2019.
  14. R. Bonalli, A. Bylard, A. Cauligi, T. Lew, and M. Pavone, “Trajectory Optimization on Manifolds: A Theoretically-Guaranteed Embedded Sequential Convex Programming Approach,” Robotics: Science and Systems, 2019.
  15. B. Ivanovic, J. Harrison, A. Sharma, M. Chen, and M. Pavone, “BaRC: Backward Reachability Curriculum for Robotic Reinforcement Learning,” Proc. IEEE Conf. on Robotics and Automation, 2019.
  16. P. Abtahi, B. Landry, J. J. Yang, M. Pavone, S. Follmer, and J. A. Landay, “Beyond The Force: Using Quadcopters to Appropriate Objects and the Environment for Haptics in Virtual Reality,” ACM CHI Conf. on Human Factors in Computing Systems, 2019.
  17. R. Bonalli, A. Cauligi, A. Bylard, and M. Pavone, “GuSTO: Guaranteed Sequential Trajectory Optimization via Sequential Convex Programming,” Proc. IEEE Conf. on Robotics and Automation, 2019.
  18. M. Tsao, D. Milojevic, C. Ruch, M. Salazar, E. Frazzoli, and M. Pavone, “Model Predictive Control of Ride-sharing Autonomous Mobility on Demand Systems,” Proc. IEEE Conf. on Robotics and Automation, 2019.
  19. T. Zahroof, A. Bylard, H. Shageer, and M. Pavone, “Perception-Constrained Robot Manipulator Planning for Satellite Servicing,” IEEE Aerospace Conference, 2019.
  20. B. Ichter and M. Pavone, “Robot Motion Planning in Learned Latent Spaces,” IEEE Robotics and Automation Letters, vol. 4, no. 3, pp. 2407--2414, 2019.
  21. R. Iglesias, F. Rossi, R. Zhang, and M. Pavone, “A BCMP Network Approach to Modeling and Controlling Autonomous Mobility-on-Demand Systems,” Int. Journal of Robotics Research, vol. 38, no. 2--3, pp. 357--374, 2019.
  22. R. Allen and M. Pavone, “A Real-Time Framework for Kinodynamic Planning in Dynamic Environments with Application to Quadrotor Obstacle Avoidance,” Robotics and Autonomous Systems, vol. 115, pp. 174--193, 2019.
  23. R. Zhang, F. Rossi, and M. Pavone, “Analysis, Control, and Evaluation of Mobility-on-Demand Systems: a Queueing-Theoretical Approach,” IEEE Transactions on Control of Network Systems, vol. 6, no. 1, pp. 115-126, 2019.
  24. E. Schmerling and M. Pavone, “Kinodynamic Planning,” Encyclopedia of Robotics, 2019.
  25. S. P. Chinchali, S. C. Livingston, M. Chen, and M. Pavone, “Multi-objective optimal control for proactive decision-making with temporal logic models,” Int. Journal of Robotics Research, vol. 38, no. 12-13, pp. 1490--1512, 2019.
2018
  1. J. Lorenzetti, M. Chen, B. Landry, and M. Pavone, “Reach-Avoid Games Via Mixed-Integer Second-Order Cone Programming,” Proc. IEEE Conf. on Decision and Control, 2018.
  2. M. Salazar, F. Rossi, M. Schiffer, C. H. Onder, and M. Pavone, “On the Interaction between Autonomous Mobility-on-Demand and the Public Transportation Systems,” Proc. IEEE Int. Conf. on Intelligent Transportation Systems, 2018.
  3. M. Tsao, R. Iglesias, and M. Pavone, “Stochastic Model Predictive Control for Autonomous Mobility on Demand,” Proc. IEEE Int. Conf. on Intelligent Transportation Systems, 2018.
  4. B. Ivanovic, E. Schmerling, K. Leung, and M. Pavone, “Generative Modeling of Multimodal Multi-Human Behavior,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2018.
  5. S. Singh, V. Sindhwani, J. J. E. Slotine, and M. Pavone, “Learning Stabilizable Dynamical Systems via Control Contraction Metrics,” Workshop on Algorithmic Foundations of Robotics, 2018.
  6. J. Harrison, A. Sharma, and M. Pavone, “Meta-Learning Priors for Efficient Online Bayesian Regression,” Workshop on Algorithmic Foundations of Robotics, 2018.
  7. B. Landry, M. Chen, S. Hemley, and M. Pavone, “Reach-Avoid Problems via Sum-of-Squares Optimization and Dynamic Programming,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2018.
  8. S. Singh, M. Chen, S. L. Herbert, C. J. Tomlin, and M. Pavone, “Robust Tracking with Model Mismatch for Fast and Safe Planning: an SOS Optimization Approach,” Workshop on Algorithmic Foundations of Robotics, 2018.
  9. M. Chen, Q. Tam, S. C. Livingston, and M. Pavone, “Signal Temporal Logic meets Hamilton-Jacobi Reachability: Connections and Applications,” Workshop on Algorithmic Foundations of Robotics, 2018.
  10. F. Rossi, R. Iglesias, M. Alizadeh, and M. Pavone, “On the Interaction Between Autonomous Mobility-on-Demand Systems and the Power Network: Models and Coordination Algorithms,” Robotics: Science and Systems, 2018.
  11. F. Rossi, S. Bandyopadhyay, M. Wolf, and M. Pavone, “Review of Multi-Agent Algorithms for Collective Behavior: a Structural Taxonomy,” IFAC Workshop on Networked & Autonomous Air & Space Systems, 2018.
  12. L. Janson, T. Hu, and M. Pavone, “Safe Motion Planning in Unknown Environments: Optimality Benchmarks and Tractable Policies,” Robotics: Science and Systems, 2018.
  13. B. Hockman and M. Pavone, “Traversability of Hopping Rovers on Small Solar System Bodies,” Int. Symp. on Artificial Intelligence, Robotics and Automation in Space, 2018.
  14. Z. Wang, S. Singh, M. Pavone, and M. Schwager, “Cooperative Object Transport in 3D with Multiple Quadrotors using No Peer Communication,” Proc. IEEE Conf. on Robotics and Automation, 2018.
  15. R. Iglesias, F. Rossi, K. Wang, D. Hallac, J. Leskovec, and M. Pavone, “Data-Driven Model Predictive Control of Autonomous Mobility-on-Demand Systems,” Proc. IEEE Conf. on Robotics and Automation, 2018.
  16. B. Ichter, J. Harrison, and M. Pavone, “Learning Sampling Distributions for Robot Motion Planning,” Proc. IEEE Conf. on Robotics and Automation, 2018.
  17. E. Schmerling, K. Leung, W. Vollprecht, and M. Pavone, “Multimodal Probabilistic Model-Based Planning for Human-Robot Interaction,” Proc. IEEE Conf. on Robotics and Automation, 2018.
  18. S. Chiodini, R. G. Reid, B. Hockman, I. A. D. Nesnas, S. Debei, and M. Pavone, “Robust Visual Localization for Hopping Rovers on Small Bodies,” Proc. IEEE Conf. on Robotics and Automation, 2018.
  19. B. Hockman, R. G. Reid, I. A. D. Nesnas, and M. Pavone, “Gravimetric Localization on the Surface of Small Bodies,” IEEE Aerospace Conference, 2018.
  20. S. Chinchali, P. Hu, T. Chu, M. Sharma, M. Bansal, R. Misra, M. Pavone, and S. Katti, “Cellular Network Traffic Scheduling with Deep Reinforcement Learning,” Proc. AAAI Conf. on Artificial Intelligence, 2018.
  21. R. Bunge, M. Pavone, and I. Kroo, “Minimal Altitude Loss Pullout Maneuvers,” AIAA Conf. on Guidance, Navigation and Control, 2018.
  22. S. Singh, Y. L. Chow, A. Majumdar, and M. Pavone, “A Framework for Time-Consistent, Risk-Sensitive Model Predictive Control: Theory and Algorithms,” IEEE Transactions on Automatic Control, vol. 64, no. 7, pp. 2905--2912, 2018.
  23. L. Janson, B. Ichter, and M. Pavone, “Deterministic Sampling-Based Motion Planning: Optimality, Complexity, and Performance,” Int. Journal of Robotics Research, vol. 37, no. 1, pp. 46--61, 2018.
  24. K. Leung, E. Schmerling, M. Chen, J. Talbot, J. C. Gerdes, and M. Pavone, “On Infusing Reachability-Based Safety Assurance within Probabilistic Planning Frameworks for Human-Robot Vehicle Interactions,” Int. Symp. on Experimental Robotics, 2018.
  25. Y. Chow, M. Ghavamzadeh, L. Janson, and M. Pavone, “Risk-Constrained Reinforcement Learning with Percentile Risk Criteria,” Journal of Machine Learning Research, vol. 18, no. 167, pp. 1--51, 2018.
  26. S. Singh, J. Lacotte, A. Majumdar, and M. Pavone, “Risk-sensitive Inverse Reinforcement Learning via Semi- and Non-Parametric Methods,” Int. Journal of Robotics Research, vol. 37, no. 13, pp. 1713--1740, 2018.
  27. F. Rossi, R. Zhang, Y. Hindy, and M. Pavone, “Routing Autonomous Vehicles in Congested Transportation Networks: Structural Properties and Coordination Algorithms,” Autonomous Robots, vol. 42, no. 7, pp. 1427--1442, 2018.
  28. S. Jorgensen, R. Chen, M. Milam, and M. Pavone, “The Team Surviving Orienteers Problem: Routing Teams of Robots in Uncertain Environments with Survival Constraints,” Autonomous Robots, vol. 42, no. 4, pp. 927--952, 2018.
2017
  1. J. Harrison, A. Garg, B. Ivanovic, Y. Zhu, S. Savarese, F. F. Li, and M. Pavone, “ADAPT: Zero-Shot Adaptive Policy Transfer for Stochastic Dynamical Systems,” Int. Symp. on Robotics Research, 2017.
  2. A. Majumdar and M. Pavone, “How Should a Robot Assess Risk? Towards an Axiomatic Theory of Risk in Robotics,” Int. Symp. on Robotics Research, 2017.
  3. S. P. Chinchali, S. C. Livingston, and M. Pavone, “Multi-objective optimal control for proactive decision-making with temporal logic models,” Int. Symp. on Robotics Research, 2017.
  4. B. Ichter, B. Landry, E. Schmerling, and M. Pavone, “Perception-Aware Motion Planning via Multiobjective Search on GPUs,” Int. Symp. on Robotics Research, 2017.
  5. B. Hockman and M. Pavone, “Stochastic Motion Planning for Hopping Rovers on Small Solar System Bodies,” Int. Symp. on Robotics Research, 2017.
  6. S. Jorgensen, R. Chen, M. Milam, and M. Pavone, “The Risk-Sensitive Coverage Problem: Multi-Robot Routing Under Uncertainty with Service Level and Survival Constraints,” Proc. IEEE Conf. on Decision and Control, 2017.
  7. S. Jorgensen, R. Chen, M. Milam, and M. Pavone, “The Matroid Team Surviving Orienteers Problem: Constrained Routing of Heterogeneous Teams with Risky Traversal,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2017.
  8. R. MacPherson, B. Hockman, A. Bylard, M. A. Estrada, M. R. Cutkosky, and M. Pavone, “Trajectory Optimization for Dynamic Grasping in Space using Adhesive Grippers,” Field and Service Robotics, 2017.
  9. E. Schmerling and M. Pavone, “Evaluating Trajectory Collision Probability through Adaptive Importance Sampling for Safe Motion Planning,” Robotics: Science and Systems, 2017.
  10. A. Majumdar, S. Singh, A. Mandlekar, and M. Pavone, “Risk-sensitive Inverse Reinforcement Learning via Coherent Risk Models,” Robotics: Science and Systems, 2017.
  11. M. A. Estrada, H. Jiang, B. Noll, E. W. Hawkes, M. Pavone, and M. R. Cutkosky, “Force and Moment Constraints of a Curved Surface Gripper and Wrist for Assistive Free Flyers,” Proc. IEEE Conf. on Robotics and Automation, 2017.
  12. B. Ichter, E. Schmerling, A. Agha-mohammadi, and M. Pavone, “Real-Time Stochastic Kinodynamic Motion Planning via Multiobjective Search on GPUs,” Proc. IEEE Conf. on Robotics and Automation, 2017.
  13. S. Singh, A. Majumdar, J. J. E. Slotine, and M. Pavone, “Robust Online Motion Planning via Contraction Theory and Convex Optimization,” Proc. IEEE Conf. on Robotics and Automation, 2017.
  14. B. Ichter, E. Schmerling, and M. Pavone, “Group Marching Tree: Sampling-Based Approximately Optimal Motion Planning on GPUs,” IEEE Int. Conf. on Robotic Computing, 2017.
  15. S. Jorgensen, R. Chen, M. Milam, and M. Pavone, “The Team Surviving Orienteers Problem: Routing Robots in Uncertain Environments with Survival Constraints,” IEEE Int. Conf. on Robotic Computing, 2017.
  16. A. Sushko, A. Tedjarati, J. Creus-Costa, S. Maldonado, K. Marshland, and M. Pavone, “Low cost, high endurance, altitude-controlled latex balloon for near-space research (ValBal),” IEEE Aerospace Conference, 2017.
  17. A. Bylard, R. MacPherson, B. Hockman, M. R. Cutkosky, and M. Pavone, “Robust Capture and Deorbit of Rocket Body Debris Using Controllable Dry Adhesion,” IEEE Aerospace Conference, 2017.
  18. J. A. Starek, E. Schmerling, G. D. Maher, B. W. Barbee, and M. Pavone, “Fast, Safe, Propellant-Efficient Spacecraft Motion Planning Under Clohessy-Wiltshire-Hill Dynamics,” AIAA Journal of Guidance, Control, and Dynamics, vol. 40, no. 2, pp. 418--438, 2017.
2016
  1. B. Hockman, R. G. Reid, I. A. D. Nesnas, and M. Pavone, “Experimental Methods for Mobility and Surface Operations of Microgravity Robots,” Int. Symp. on Experimental Robotics, 2016.
  2. J. A. Starek, B. Acikmese, I. A. D. Nesnas, and M. Pavone, “Spacecraft Autonomy Challenges for Next Generation Space Missions,” Advances in Control System Technology for Aerospace Applications, 2016.
  3. I. B. Flader, C. H. Ahn, D. D. Gerrard, E. J. Ng, Y. Yang, V. A. Hong, M. Pavone, and T. W. Kenny, “Autonomous calibration of MEMS disk resonating gyroscope for improved sensor performance,” American Control Conference, 2016.
  4. R. Zhang, F. Rossi, and M. Pavone, “Routing Autonomous Vehicles in Congested Transportation Networks: Structural Properties and Coordination Algorithms,” Robotics: Science and Systems, 2016.
  5. M. A. Estrada, B. Hockman, A. Bylard, E. W. Hawkes, M. R. Cutkosky, and M. Pavone, “Free-Flyer Acquisition of Spinning Objects with Gecko-Inspired Adhesives,” Proc. IEEE Conf. on Robotics and Automation, 2016.
  6. R. Zhang, F. Rossi, and M. Pavone, “Model Predictive Control of Autonomous Mobility-on-Demand Systems,” Proc. IEEE Conf. on Robotics and Automation, 2016.
  7. Z. Sunberg, M. Kochenderfer, and M. Pavone, “Optimized and Trusted Collision Avoidance for Unmanned Aerial Vehicles using Approximate Dynamic Programming,” Proc. IEEE Conf. on Robotics and Automation, 2016.
  8. S. Carpin, Y. Chow, and M. Pavone, “Risk Aversion in Finite Markov Decision Processes Using Total Cost Criteria and Average Value at Risk,” Proc. IEEE Conf. on Robotics and Automation, 2016.
  9. S. P. Chinchali, S. C. Livingston, M. Pavone, and J. W. Burdick, “Simultaneous Model Identification and Task Satisfaction in the Presence of Temporal Logic Constraints,” Proc. IEEE Conf. on Robotics and Automation, 2016.
  10. J. A. Starek, E. Schmerling, G. D. Maher, B. W. Barbee, and M. Pavone, “Real-Time, Propellant-Optimized Spacecraft Motion Planning under Clohessy-Wiltshire-Hill Dynamics,” IEEE Aerospace Conference, 2016.
  11. R. Allen and M. Pavone, “A Real-Time Framework for Kinodynamic Planning with Application to Quadrotor Obstacle Avoidance,” AIAA Conf. on Guidance, Navigation and Control, 2016.
  12. R. Iglesias, F. Rossi, R. Zhang, and M. Pavone, “A BCMP Network Approach to Modeling and Controlling Autonomous Mobility-on-Demand Systems,” Workshop on Algorithmic Foundations of Robotics, 2016.
  13. R. Zhang and M. Pavone, “Control of Robotic Mobility-on-Demand Systems: A Queueing-Theoretical Perspective,” Int. Journal of Robotics Research, vol. 35, no. 1--3, pp. 186--203, 2016.
  14. B. Hockman, A. Frick, I. A. D. Nesnas, and M. Pavone, “Design, Control, and Experimentation of Internally-Actuated Rovers for the Exploration of Low-Gravity Planetary Bodies,” Journal of Field Robotics, vol. 34, no. 1, pp. 5--24, 2016.
  15. K. Leung, E. Schmerling, and M. Pavone, “Distributional Prediction of Human Driving Behaviours using Mixture Density Networks,” Stanford University, 2016.
  16. R. Allen, M. Pavone, and M. Schwager, “Flying Smartphones: When Portable Computing Sprouts Wings,” IEEE Pervasive Computing, vol. 15, no. 3, pp. 83--88, 2016.
2015
  1. Z. Zhu, E. Schmerling, and M. Pavone, “A Convex Optimization Approach to Smooth Trajectories for Motion Planning with Car-Like Robots,” Proc. IEEE Conf. on Decision and Control, 2015.
  2. E. Schmerling, L. Janson, and M. Pavone, “Optimal Sampling-Based Motion Planning under Differential Constraints: the Drift Case with Linear Affine Dynamics,” Proc. IEEE Conf. on Decision and Control, 2015.
  3. S. Singh, S. D'Amico, and M. Pavone, “High-Fidelity Modeling and Control System Synthesis for a Drag-Free Microsatellite,” Int. Symp. on Space Flight Dynamics, 2015.
  4. J. A. Starek, J. V. Gomez, E. Schmerling, L. Janson, L. Moreno, and M. Pavone, “An Asymptotically-Optimal Sampling-Based Algorithm for Bi-directional Motion Planning,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2015.
  5. L. Janson, B. Ichter, and M. Pavone, “Deterministic Sampling-Based Motion Planning: Optimality, Complexity, and Performance,” Int. Symp. on Robotics Research, 2015.
  6. L. Janson, E. Schmerling, and M. Pavone, “Monte Carlo Motion Planning for Robot Trajectory Optimization Under Uncertainty,” Int. Symp. on Robotics Research, 2015.
  7. R. Zhang and M. Pavone, “A Queueing Network Approach to the Analysis and Control of Mobility-on-Demand Systems,” American Control Conference, 2015.
  8. R. Zhang, K. Spieser, E. Frazzoli, and M. Pavone, “Models, Algorithms and Evaluation for Autonomous Mobility-on-Demand Systems,” American Control Conference, 2015.
  9. S. Singh, E. Schmerling, and M. Pavone, “Decentralized Algorithms for 3D Symmetric Formations in Robotic Networks - A Contraction Theory Approach,” Proc. IEEE Conf. on Robotics and Automation, 2015.
  10. E. Schmerling, L. Janson, and M. Pavone, “Optimal Sampling-Based Motion Planning under Differential Constraints: the Driftless Case,” Proc. IEEE Conf. on Robotics and Automation, 2015.
  11. R. Allen and M. Pavone, “Toward A Real-Time Framework for Solving the Kinodynamic Motion Planning Problem,” Proc. IEEE Conf. on Robotics and Automation, 2015.
  12. J. A. Starek, B. W. Barbee, and M. Pavone, “A Sampling-Based Approach to Spacecraft Autonomous Maneuvering with Safety Specifications,” AAS GN&C Conference, 2015.
  13. M. Pavone, “Autonomous Mobility-on-Demand Systems for Future Urban Mobility,” Autonomes Fahren, 2015.
  14. M. Ono, M. Pavone, Y. Kuwata, and J. Balaram, “Chance-Constrained Dynamic Programming with Application to Risk-Aware Robotic Space Exploration,” Autonomous Robots, vol. 39, no. 4, pp. 555--571, 2015.
  15. B. Hockman, A. Frick, I. A. D. Nesnas, and M. Pavone, “Design, Control, and Experimentation of Internally-Actuated Rovers for the Exploration of Low-Gravity Planetary Bodies,” Field and Service Robotics, 2015.
  16. L. Janson, E. Schmerling, A. Clark, and M. Pavone, “Fast Marching Tree: A Fast Marching Sampling-Based Method for Optimal Motion Planning in Many Dimensions,” Int. Journal of Robotics Research, vol. 34, no. 7, pp. 883--921, 2015.
  17. Y. Chow, A. Tamar, S. Mannor, and M. Pavone, “Risk-Sensitive and Robust Decision-Making: a CVaR Optimization Approach,” Conf. on Neural Information Processing Systems, 2015.
2014
  1. F. Rossi and M. Pavone, “On the Fundamental Limitations of Performance for Distributed Decision-Making in Robotic Networks,” Proc. IEEE Conf. on Decision and Control, 2014.
  2. R. Allen, A. Clark, J. A. Starek, and M. Pavone, “A Machine Learning Approach for Real-time Computation of Dynamical System Reachability Sets,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2014.
  3. S. Carpin, M. Pavone, and B. M. Sadler, “Rapid Multirobot Deployment with Time Constraints,” IEEE/RSJ Int. Conf. on Intelligent Robots & Systems, 2014.
  4. R. Zhang and M. Pavone, “Control of Robotic Mobility-on-Demand Systems: a Queueing-Theoretical Perspective,” Robotics: Science and Systems, 2014.
  5. Y. Chow and M. Pavone, “A Framework for Time-Consistent, Risk-Averse Model Predictive Control: Theory and Algorithms,” American Control Conference, 2014.
  6. R. G. Reid, L. Roveda, I. A. D. Nesnas, and M. Pavone, “Contact Dynamics of Internally-Actuated Platforms for the Exploration of Small Solar System Bodies,” Int. Symp. on Artificial Intelligence, Robotics and Automation in Space, 2014.
  7. A. W. Koenig, M. Pavone, J. C. Castillo-Rogez, and I. A. D. Nesnas, “A Dynamical Characterization of Internally-Actuated Microgravity Mobility Systems,” Proc. IEEE Conf. on Robotics and Automation, 2014.
  8. F. Rossi and M. Pavone, “Distributed Consensus with Mixed Time/Communication Bandwidth Performance Metrics,” Allerton Conf. on Communications, Control and Computing, 2014.
  9. E. Frazzoli and M. Pavone, “Multi-Vehicle Routing,” Encyclopedia of Systems and Control, 2014.
  10. K. Spieser, K. Treleaven, R. Zhang, E. Frazzoli, D. Morton, and M. Pavone, “Toward a Systematic Approach to the Design and Evaluation of Autonomous Mobility-on-Demand Systems: A Case Study in Singapore,” Road Vehicle Automation, 2014.
  11. Y. Chow, M. Pavone, B. M. Sadler, and S. Carpin, “Trading Safety Versus Performance: Rapid Deployment of Robotic Swarms with Robust Performance Constraints,” ASME Journal of Dynamic Systems, Measurement, and Control, vol. 137, no. 3, pp. 031005.1--031005.11, 2014.
2013
  1. Y. Chow and M. Pavone, “A Uniform-Grid Discretization Algorithm for Stochastic Optimal Control with Risk Constraints,” Proc. IEEE Conf. on Decision and Control, 2013.
  2. L. Janson and M. Pavone, “Fast Marching Trees: A Fast Marching Sampling-Based Method for Optimal Motion Planning in Many Dimensions,” Int. Symp. on Robotics Research, 2013.
  3. F. Rossi and M. Pavone, “Decentralized Decision-Making on Robotic Networks with Hybrid Performance Metrics,” Allerton Conf. on Communications, Control and Computing, 2013.
  4. J. J. Enright, E. Frazzoli, M. Pavone, and K. Savla, “UAV Routing and Coordination in Stochastic, Dynamic Environments,” Handbook of Unmanned Aerial Vehicles, 2013.
  5. S. L. Smith, M. Pavone, M. Schwager, E. Frazzoli, and D. Rus, “Rebalancing the Rebalancers: Optimally Routing Vehicles and Drivers in Mobility-on-Demand Systems,” American Control Conference, 2013.
  6. Y. Chow and M. Pavone, “Stochastic Optimal Control with Dynamic, Time-Consistent Risk Constraints,” American Control Conference, 2013.
  7. R. Allen, M. Pavone, C. McQuin, I. Nesnas, J. C. Castillo-Rogez, T. N. Nguyen, and J. A. Hoffman, “Internally-Actuated Rovers for All-Access Surface Mobility: Theory and Experimentation,” Proc. IEEE Conf. on Robotics and Automation, 2013.
  8. M. Pavone, J. Castillo, I. Nesnas, J. A. Hoffman, and N. Strange, “Spacecraft/Rover Hybrids for the Exploration of Small Solar System Bodies,” IEEE Aerospace Conference, 2013.
  9. K. Treleaven, M. Pavone, and E. Frazzoli, “Asymptotically Optimal Algorithms for One-to-One Pickup and Delivery Problems with Applications to Transportation Systems,” IEEE Transactions on Automatic Control, vol. 58, no. 9, pp. 2261--2276, 2013.
  10. M. Quadrelli, M. McHenry, B. Wilcox, J. Hall, R. Volpe, I. Nesnas, H. Nayar, P. Backes, R. Mukherjee, L. Matthies, W. Zimmerman, D. Mittman, M. Pavone, and A. Elfes, “Guidance, Navigation, and Control Technology Assessment for Future Planetary Science Missions Part III, Surface Guidance, Navigation, and Control,” Planetary Science Division, NASA Science Mission Directorate, 2013.
2012
  1. Y. Kuwata, M. Pavone, and J. Balaram, “A Risk-Constrained Multi-Stage Decision Making Approach to the Architectural Analysis of Mars Missions,” Proc. IEEE Conf. on Decision and Control, 2012.
  2. K. Treleaven, M. Pavone, and E. Frazzoli, “Models and Efficient Algorithms for Pickup and Delivery Problems on Roadmaps,” Proc. IEEE Conf. on Decision and Control, 2012.
  3. K. Treleaven, M. Pavone, and E. Frazzoli, “Cost Bounds for Pickup and Delivery Problems with Application to Large-Scale Transportation Systems,” American Control Conference, 2012.
  4. A. Stoica, C. Assad, M. Wolf, K. S. You, M. Pavone, T. Huntsberger, and Y. Iwashita, “Using Arm and Hand Gestures to Command Robots during Stealth Operations,” Proc. of SPIE, 2012.
  5. J. Castillo, M. Pavone, I. Nesnas, and J. A. Hoffman, “Expected Science Return of Spatially-Extended In-Situ Exploration at Small Solar System Bodies,” IEEE Aerospace Conference, 2012.
  6. M. Pavone, S. L. Smith, E. Frazzoli, and D. Rus, “Robotic Load Balancing for Mobility-on-Demand Systems,” Int. Journal of Robotics Research, vol. 31, no. 7, pp. 839--854, 2012.
  7. M. Pavone, J. Castillo, J. A. Hoffman, and I. Nesnas, “Spacecraft/Rover Hybrids for the Exploration of Small Solar System Bodies,” NASA NIAC Program, 2012.
2011
  1. K. Treleaven, M. Pavone, and E. Frazzoli, “An Asymptotically Optimal Algorithm for Pickup and Delivery Problems,” Proc. IEEE Conf. on Decision and Control, 2011.
  2. M. Pavone, S. L. Smith, E. Frazzoli, and D. Rus, “Load Balancing for Mobility-on-Demand Systems,” Robotics: Science and Systems, 2011.
  3. M. Pavone, E. Frazzoli, and F. Bullo, “Adaptive and Distributed Algorithms for Vehicle Routing in a Stochastic and Dynamic Environment,” IEEE Transactions on Automatic Control, vol. 56, no. 6, pp. 1259--1274, 2011.
  4. M. Pavone, A. Arsie, E. Frazzoli, and F. Bullo, “Distributed Algorithms for Environment Partitioning in Mobile Robotic Networks,” IEEE Transactions on Automatic Control, vol. 56, no. 8, pp. 1834--1848, 2011.
  5. F. Bullo, E. Frazzoli, M. Pavone, K. Savla, and S. L. Smith, “Dynamic Vehicle Routing for Robotic Systems,” Proc. of the IEEE, vol. 99, no. 9, pp. 1482--1504, 2011.
2010
  1. M. Pavone, K. Treleaven, and E. Frazzoli, “Fundamental Performance Limits and Efficient Policies for Transportation-On-Demand Systems,” Proc. IEEE Conf. on Decision and Control, 2010.
  2. M. Pavone, “Dynamic Vehicle Routing for Robotic Networks,” Ph.D. dissertation, Massachusetts Inst. of Technology, Dept. of Aeronautics and Astronautics, 2010.
  3. M. Pavone and E. Frazzoli, “Dynamic Vehicle Routing with Stochastic Time Constraints,” Proc. IEEE Conf. on Robotics and Automation, 2010.
  4. J. L. Ramirez, M. Pavone, E. Frazzoli, and D. W. Miller, “Distributed Control of Spacecraft Formations via Cyclic Pursuit: Theory and Experiments,” AIAA Journal of Guidance, Control, and Dynamics, vol. 33, no. 5, pp. 1655--1669, 2010.
  5. S. L. Smith, M. Pavone, F. Bullo, and E. Frazzoli, “Dynamic Vehicle Routing with Priority Classes of Stochastic Demands,” SIAM Journal on Control and Optimization, vol. 48, no. 5, pp. 3224--3245, 2010.
2009
  1. J. L. Ramirez, M. Pavone, E. Frazzoli, and D. W. Miller, “Distributed Control of Spacecraft Formation via Cyclic Pursuit: Theory and Experiments,” American Control Conference, 2009.
  2. M. Pavone, S. L. Smith, F. Bullo, and E. Frazzoli, “Dynamic Multi-Vehicle Routing with Multiple Classes of Demands,” American Control Conference, 2009.
  3. M. Pavone, A. Arsie, E. Frazzoli, and F. Bullo, “Equitable Partitioning Policies for Robotic Networks,” Proc. IEEE Conf. on Robotics and Automation, 2009.
  4. M. Pavone, N. Bisnik, E. Frazzoli, and V. Isler, “A Stochastic and Dynamic Vehicle Routing Problem with Time Windows and Customer Impatience,” Journal of Mobile Networks and Applications, vol. 14, no. 3, pp. 350--364, 2009.
  5. M. Pavone, K. Savla, and E. Frazzoli, “Sharing the Load,” IEEE Robotics and Automation Magazine, vol. 16, no. 2, pp. 52--61, 2009.
2008
  1. M. Pavone, E. Frazzoli, and F. Bullo, “Distributed Policies for Equitable Partitioning: Theory and Applications,” Proc. IEEE Conf. on Decision and Control, 2008.
  2. S. L. Smith, M. Pavone, F. Bullo, and E. Frazzoli, “Dynamic Vehicle Routing with Heterogeneous Demands,” Proc. IEEE Conf. on Decision and Control, 2008.
2007
  1. M. Pavone, E. Frazzoli, and F. Bullo, “Decentralized Algorithms for Stochastic and Dynamic Vehicle Routing with General Demand Distribution,” Proc. IEEE Conf. on Decision and Control, 2007.
  2. M. Pavone, N. Bisnik, E. Frazzoli, and V. Isler, “Decentralized Vehicle Routing in a Stochastic and Dynamic Environment with Customer Impatience,” Int. Conf. on Robot Communication and Coordination, 2007.
  3. M. Pavone and E. Frazzoli, “Decentralized Policies for Geometric Pattern Formation,” American Control Conference, 2007.
  4. M. Pavone and E. Frazzoli, “Decentralized Policies for Geometric Pattern Formation and Path Coverage,” ASME Journal of Dynamic Systems, Measurement, and Control, vol. 129, no. 5, pp. 633--643, 2007.
2006
  1. P. Arena, L. Fortuna, M. Frasca, L. Patanè, and M. Pavone, “Realization of a CNN-Driven Cockroach-Inspired Robot,” Int. Symp. on Circuits and Systems, 2006.
  2. P. Arena, L. Fortuna, M. Frasca, L. Patanè, and M. Pavone, “Towards Autonomous Adaptive Behavior in a Bio-inspired CNN-controlled Robot,” Int. Symp. on Circuits and Systems, 2006.
  3. M. Pavone, P. Arena, and L. Patanè, “An Innovative Mechanical and Control Architecture for a Biomimetic Hexapod for Planetary Exploration,” Space Technology, vol. 26, no. 1-2, pp. 13--24, 2006.
  4. M. Pavone, P. Arena, L. Fortuna, M. Frasca, and L. Patanè, “Climbing Obstacle in Bio-robots via CNN and Adaptive Attitude Control,” Int. Journal of Circuit Theory and Applications, vol. 34, no. 1, pp. 109--125, 2006.
2005
  1. M. Pavone, P. Arena, and L. Patanè, “An Innovative Mechanical and Control Architecture for a Biomimetic Hexapod for Planetary Exploration,” Int. Astronautical Congress, 2005.
  2. P. Arena, L. Fortuna, M. Frasca, L. Patanè, and M. Pavone, “Climbing Obstacles via Bio-Inspired CNN-CPG and Adaptive Attitude Control,” Int. Symp. on Circuits and Systems, 2005.