Poster Session 1 (June 23, Thursday, 13:00-14:00)
Poster # | Paper # | Authors | Paper Title |
1 | 33 | Stephen Tu, Alexander Robey, Tingnan Zhang and Nikolai Matni | On the Sample Complexity of Stability Constrained Imitation Learning |
2 | 110 | Amir Khazraei, Henry Pfister and Miroslav Pajic | Resiliency of Perception-Based Controllers Against Attacks |
3 | 146 | Saber Jafarpour, Matthew Abate, Alexander Davydov, Francesco Bullo and Samuel Coogan | Robustness Certificates for Implicit Neural Networks: A Mixed Monotone Contractive Approach |
4 | 7 | Steven Morad, Stephan Liwicki, Ryan Kortvelesy, Roberto Mecca and Amanda Prorok | Modeling Partially Observable Systems using Graph-Based Memory and Topological Priors |
5 | 6 | Anirudh Vemula, Wen Sun, Maxim Likhachev and J. Andrew Bagnell | On the Effectiveness of Iterative Learning Control |
6 | 4 | Ting-Han Fan, Xian Yeow Lee and Yubo Wang | PowerGym: A Reinforcement Learning Environment for Volt-Var Control in Power Distribution Systems |
7 | 54 | Samuel Low | Optimizing Pointing Sequences with Resource Constraints in Large Satellite Formations using Reinforcement Learning |
8 | 141 | Daniel Gurevich, Debdipta Goswami, Charles L. Fefferman and Clarence W. Rowley | Optimal Control with Learning on the Fly: System with Unknown Drift |
9 | 170 | Thomas Lew, Lucas Janson, Riccardo Bonalli and Marco Pavone | A Simple and Efficient Sampling-based Algorithm for General Reachability Analysis |
10 | 32 | Yuda Song, Yuan Ye, Wen Sun and Kris Kitani | Online No-regret Model-Based Meta RL for Personalized Navigation |
11 | 46 | Yansong Li and Shuo Han | Accelerating Model-Free Policy Optimization Using Model-Based Gradient: A Composite Optimization Perspective |
12 | 56 | Yifeng Jiang, Jiazheng Sun and C. Karen Liu | Data-Augmented Contact Model for Rigid Body Simulation |
13 | 160 | Muhammed Sayin and Kemal Cetiner | On the Heterogeneity of Independent Learning Dynamics in Zero-sum Stochastic Games |
14 | 147 | Julian Viereck, Avadesh Meduri and Ludovic Righetti | ValueNetQP: Learned one-step optimal control for legged locomotion |
15 | 117 | Ningyuan Zhang, Wenliang Liu and Calin Belta | Distributed Control using Reinforcement Learning with Temporal-Logic-Based Reward Shaping |
16 | 106 | Zhe Du, Necmiye Ozay and Laura Balzano | Clustering-based Mode Reduction for Markov Jump Systems |
17 | 87 | Saul Santos, Monica Ekal and Rodrigo Ventura | Symplectic Momentum Neural Networks – Using Discrete Variational Mechanics as a prior in Deep Learning |
18 | 88 | Charis Stamouli, Anastasios Tsiamis, Manfred Morari and George J. Pappas | Adaptive Stochastic MPC under Unknown Noise Distribution |
19 | 34 | Thinh Doan | Convergence Rates of Two-Time-Scale Gradient Descent-Ascent Dynamics for Solving Nonconvex Min-Max Problems |
20 | 113 | Tianhao Wei and Changliu Liu | Safe Control with Neural Network Dynamic Models |
21 | 148 | Yifei Zhang, Sourav Ukil, Ephraim Neimand, Serban Sabau and Myron Hohil | Sample Complexity of the Robust LQG Regulator with Coprime Factors Uncertainty |
22 | 108 | Marcos Vasconcelos | Learning distributed channel access policies for networked estimation: data-driven optimization in the mean-field regime |
23 | 73 | Vittorio Caggiano, Huawei Wang, Guillaume Durandau, Massimo Sartori and Vikash Kumar | MyoSuite: A contact-rich simulation suite for musculoskeletal motor control |
24 | 41 | Franck Djeumou, Cyrus Neary, Eric Goubault, Sylvie Putot and Ufuk Topcu | Neural Networks with Physics-Informed Architectures and Constraints for Dynamical Systems Modeling |
Poster Session 2 (June 23, Thursday, 16:15-17:15)
Poster # | Paper # | Authors | Paper Title |
1 | 19 | Haitong Ma, Changliu Liu, Shengbo Eben Li, Sifa Zheng and Jianyu Chen | Joint Synthesis of Safety Certificate and Safe Control Policy using Constrained Reinforcement Learning |
2 | 21 | Samarth Sinha, Jiaming Song, Animesh Garg and Stefano Ermon | Experience Replay with Likelihood-free Importance Weights |
3 | 40 | Cameron R. Wolfe and Anastasios Kyrillidis | i-SpaSP: Structured Neural Pruning via Sparse Signal Recovery |
4 | 51 | Yuanhanqing Huang and Jianghai Hu | Distributed Stochastic Nash Equilibrium Learning in Locally Coupled Network Games with Unknown Parameters |
5 | 94 | Rameez Wajid, Asad Ullah Awan and Majid Zamani | Formal Synthesis of Safety Controllers for Unknown Stochastic Control Systems using Gaussian Process Learning |
6 | 165 | Ivan Dario Jimenez Rodriguez, Noel Csomay-Shanklin, Yisong Yue and Aaron D. Ames | Neural Gaits: Learning Bipedal Locomotion via Control Barrier Functions and Zero Dynamics Policies |
7 | 1 | Daniel Jung | Automated Design of Grey-Box Recurrent Neural Networks For Fault Diagnosis using Structural Models and Causal Information |
8 | 17 | Olle Kjellqvist and Anders Rantzer | Learning-Enabled Robust Control with Noisy Measurements |
9 | 59 | Gautam Goel and Babak Hassibi | Online estimation and control with optimal pathlength regret |
10 | 69 | Franck Djeumou and Ufuk Topcu | Learning How to Reach, Swim, Walk and Fly in One Trial: Control of Unknown Systems with Scarce Data and Side Information |
11 | 83 | Agustin Castellano, Hancheng Min, Enrique Mallada and Juan Andrés Bazerque | Reinforcement Learning with Almost Sure Constraints |
12 | 142 | Lukas Brunke, Siqi Zhou and Angela P. Schoellig | Barrier Bayesian Linear Regression: Online Learning of Control Barrier Conditions for Safety-Critical Control of Uncertain Systems |
13 | 180 | Brett Lopez and Jean-Jacques Slotine | Adaptive Variants of Optimal Feedback Policies |
14 | 167 | Raghu Arghal, Eric Lei and Shirin Saeedi Bidokhti | Robust Graph Neural Networks via Probabilistic Lipschitz Constraints |
15 | 143 | Yuchen Cui, Scott Niekum, Abhinav Gupta, Vikash Kumar and Aravind Rajeswaran | Can Foundation Models Perform Zero-Shot Task Specification For Robot Manipulation? |
16 | 70 | Feiran Zhao, Xingchen Li and Keyou You | Data-driven Control of Unknown Linear Systems via Quantized Feedback |
17 | 61 | Ce Xu Zheng, Adrià Colomé, Luis Sentis and Carme Torras | Mixtures of Controlled Gaussian Processes for Dynamical Modeling of Deformable Objects |
18 | 78 | Santiago Sanchez-Escalonilla Plaza, Rodolfo Reyes-Baez and Bayu Jayawardhana | Total Energy Shaping with Neural Interconnection and Damping Assignment – Passivity Based Control |
19 | 163 | Junhyung Lyle Kim, Panos Toulis and Anastasios Kyrillidis | Convergence and Stability of the Stochastic Proximal Point Algorithm with Momentum |
20 | 171 | Felipe Galarza-Jiménez, Jorge Poveda and Emiliano Dall’Anese | Sliding-Seeking Control:Model-Free Optimization with Hard Constraints |
21 | 172 | Bibit Bianchini, Mathew Halm, Nikolai Matni and Michael Posa | Generalization Bounds for Implicit Learning of Nearly Discontinuous Functions |
22 | 5 | Abhishek Cauligi, Ankush Chakrabarty, Stefano Di Cairano and Rien Quirynen | Recurrent Neural Networks and Presolve Methods for Fast Mixed-integer Optimal Control |
23 | 93 | Shagun Sodhani, Franziska Meier, Joellw Pineau and Amy Zhang | Block Contextual MDPs for Continual Learning |
24 | 162 | Ryan Cosner, Maegan Tucker, Andrew Taylor, Kejun Li, Tamas Molnar, Wyatt Ubelacker, Anil Alan, Gabor Orosz, Yisong Yue and Aaron Ames | Safety-Aware Preference-Based Learning for Safety-Critical Control |
Poster Session 3 (June 24, Friday, 11:00-12:00)
Poster # | Paper # | Authors | Paper Title |
1 | 86 | Luca Furieri, Clara Lucía Galimberti, Muhammad Zakwan and Giancarlo Ferrari-Trecate | Distributed neural network control with dependability guarantees: a compositional port-Hamiltonian approach |
2 | 140 | Horia Mania, Ali Jadbabaie, Devavrat Shah and Suvrit Sra | Time varying regression with hidden linear dynamics |
3 | 144 | Riccardo Valperga, Kevin Webster, Dmitry Turaev, Victoria Klein and Jeroen Lamb | Structure-preserving time-reversible symplectic neural networks for learning dynamical systems |
4 | 55 | Krista Longi, Jakob Lindinger, Olaf Duennbier, Melih Kandemir, Arto Klami and Barbara Rakitsch | Traversing Time with Multi-Resolution Gaussian Process State-Space Models |
5 | 68 | Ali Salamati and Majid Zamani | Data-Driven Safety Verification of Stochastic Systems via Barrier Certificates: A Wait-and-Judge Approach |
6 | 72 | Rel Guzman, Rafael Oliveira and Fabio Ramos | Adaptive Model Predictive Control by Learning Classifiers |
7 | 79 | Thomas Zhang, Stephen Tu, Nicholas Boffi, Jean-Jacques Slotine and Nikolai Matni | Adversarially Robust Stability Certificates can be Sample-Efficient |
8 | 80 | Harish S. Bhat, Kevin Collins, Prachi Gupta and Christine M. Isborn | Dynamic Learning of Correlation Potentials for a Time-Dependent Kohn-Sham System |
9 | 99 | Alan Yang, Jie Xiong, Maxim Raginsky and Elyse Rosenbaum | Input-to-State Stable Neural Ordinary Differential Equations with Applications to Transient Modeling of Circuits |
10 | 112 | Andrea Martin, Luca Furieri, Florian Dörfler, John Lygeros and Giancarlo Ferrari Trecate | Safe Control with Minimal Regret |
11 | 161 | Jose Luis Vazquez Espinoza, Alexander Liniger, Wilko Schwarting, Daniela Rus and Luc Van Gool | Deep Interactive Motion Prediction and Planning: Playing Games with Motion Prediction Models |
12 | 126 | Adam Thorpe, Thomas Lew, Meeko Oishi and Marco Pavone | Data-Driven Chance Constrained Control using Kernel Distribution Embeddings |
13 | 154 | Zhichao Li, Thai Duong and Nikolay Atanasov | Safe Autonomous Navigation for Systems with Learned SE(3) Hamiltonian Dynamics |
14 | 103 | Rahul Singh, Keuntaek Lee and Yongxin Chen | Sample-based Distributional Policy Gradient |
15 | 181 | Wanxin Jin, Alp Aydinoglu, Mathew Halm and Michael Posa | Learning Linear Complementarity Systems |
16 | 182 | Jan Brüdigam, Martin Schuck, Alexandre Capone, Stefan Sosnowski and Sandra Hirche | Structure-Preserving Learning Using Gaussian Processes and Variational Integrators |
17 | 151 | Ryan Sander, Wilko Schwarting, Tim Seyde, Igor Gilitschenski, Sertac Karaman and Daniela Rus | Neighborhood Mixup Experience Replay: Local Convex Interpolation for Improved Sample Efficiency in Continuous Control Tasks |
18 | 152 | Suhail Alsalehi, Erfan Aasi, Ron Weiss and Calin Belta | Learning Spatio-Temporal Specifications for Dynamical Systems |
19 | 37 | Henk van Waarde and Rodolphe Sepulchre | Training Lipschitz continuous operators using reproducing kernels |
20 | 42 | Siliang Zeng, Tianyi Chen, Alfredo Garcia and Mingyi Hong | Learning to Coordinate in Multi-Agent Systems: A Coordinated Actor-Critic Algorithm and Finite-Time Guarantees |
21 | 49 | Yujie Yang, Jianyu Chen and Shengbo Li | Learning POMDP Models with Similarity Space Regularization: a Linear Gaussian Case Study |
22 | 65 | Han Wang and James Anderson | Learning Linear Models Using Distributed Iterative Hessian Sketching |
23 | 16 | Andrea Sassella, Valentina Breschi and Simone Formentin | Noise handling in data-driven predictive control: a strategy based on dynamic mode decomposition |
24 | 129 | Samuel Chevalier, Jochen Stiasny and Spyros Chatzivasileiadis | Accelerating Dynamical System Simulations with Contracting and Physics-Projected Neural-Newton Solvers |
Poster Session 4 (June 24, Friday, 15:15 – 16:15)
Poster # | Paper # | Authors | Paper Title |
1 | 48 | Miguel Jaques, Martin Asenov, Michael Burke and Timothy Hospedales | Vision-based system identification and 3D keypoint discovery using dynamics constraints |
2 | 76 | Weiming Zhi, Tin Lai, Lionel Ott and Fabio Ramos | Diffeomorphic Transforms for Generalised Imitation Learning |
3 | 27 | Simon Muntwiler, Kim P. Wabersich and Melanie N. Zeilinger | Learning-based Moving Horizon Estimation through Differentiable Convex Optimization Layers |
4 | 24 | Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt and Justin Bayer | Tracking and Planning with Spatial World Models |
5 | 36 | Brendon G. Anderson and Somayeh Sojoudi | Certified Robustness via Locally Biased Randomized Smoothing |
6 | 124 | Zihao Zhou, Xingyi Yang, Ryan Rossi, Handong Zhao and Rose Yu | Neural Point Process for Learning Spatiotemporal Event Dynamics |
7 | 184 | Udaya Ghai, Xinyi Chen, Elad Hazan and Alexandre Megretski | Robust Online Control with Model Misspecification |
8 | 44 | Samuel Pfrommer, Tanmay Gautam, Alec Zhou and Somayeh Sojoudi | Safe Reinforcement Learning with Chance-constrained Model Predictive Control |
9 | 26 | Nicola Bastianello, Andrea Simonetto and Emiliano Dall’Anese | OpReg-Boost: Learning to Accelerate Online Algorithms with Operator Regression |
10 | 122 | Ameneh Nejati, Bingzhuo Zhong, Marco Caccamo and Majid Zamani | Data-Driven Controller Synthesis of Unknown Nonlinear Polynomial Systems via Control Barrier Certificates |
11 | 98 | Benjamin Gravell, Iman Shames and Tyler Summers | Robust Data-Driven Output Feedback Control via Bootstrapped Multiplicative Noise |
12 | 132 | Ross Drummond, Stephen Duncan, Mathew Turner, Patricia Pauli and Frank Allgower | Bounding the difference between model predictive control and neural networks |
13 | 138 | Zhigen Zhao, Simiao Zuo, Tuo Zhao and Ye Zhao | Adversarially Regularized Policy Learning Guided by Trajectory Optimization |
14 | 95 | Nima Eshraghi and Ben Liang | Improving Dynamic Regret in Distributed Online Mirror Descent Using Primal and Dual Information |
15 | 39 | Liliaokeawawa Cothren, Gianluca Bianchin and Emiliano Dall’Anese | Data-enabled Gradient Flow as Feedback Controller: Regulation of Linear Dynamical Systems to Minimizers of Unknown Functions |
16 | 57 | Jingrong Wang and Ben Liang | Gradient and Projection Free Distributed Online Min-Max Resource Optimization |
17 | 133 | Milad Farsi, Yinan Li, Ye Yuan and Jun Liu | A Piecewise Learning Framework for Control of Nonlinear Systems with Stability Guarantees |
18 | 164 | Francesco De Lellis, Marco Coraggio, Giovanni Russo, Mirco Musolesi and Mario di Bernardo | Control-Tutored Reinforcement Learning: Towards the Integration of Data-Driven and Model-Based Control |