Somil Bansal
収録論文 50本 ・ フィジカルAI/ロボット学習
※arXiv著者名で収集。同姓同名の別人の論文が含まれる場合があります。
論文
- Offline Policy Evaluation for Manipulation Policies via Discounted Liveness Formulation2026/5/1
- Neural Backward Reach-Avoid Tubes with MPC Supervision for High-Dimensional Systems: An Application to Safe Spacecraft Docking2026/5/1
- Cooptimizing Safety and Performance Using Safety Value-Constrained Model Predictive Control2026/4/1
- Boundary Sampling to Learn Predictive Safety Filters via Pontryagin's Maximum Principle2026/4/1
- From Words to Safety: Language-Conditioned Safety Filtering for Robot Navigation2025/11/1
- Using Language Models as Closed-Loop High-Level Planners for Robotics Applications: A Brief Overview and Benchmarks2025/11/1
- Robust Verification of Controllers under State Uncertainty via Hamilton-Jacobi Reachability Analysis2025/11/1
- MADR: MPC-guided Adversarial DeepReach2025/10/1
- MAD-PINN: A Decentralized Physics-Informed Machine Learning Framework for Safe and Optimal Multi-Agent Control2025/9/1
- Safety-Aware Imitation Learning via MPC-Guided Disturbance Injection2025/8/1
- Safety Evaluation of Motion Plans Using Trajectory Predictors as Forward Reachable Set Estimators2025/7/1
- Safe and Performant Deployment of Autonomous Systems via Model Predictive Control and Hamilton-Jacobi Reachability Analysis2025/6/1
- Unsupervised Discovery of Failure Taxonomies from Deployment Logs2025/6/1
- Bridging Model Predictive Control and Deep Learning for Scalable Reachability Analysis2025/5/1
- Reachability Barrier Networks: Learning Hamilton-Jacobi Solutions for Smooth and Flexible Control Barrier Functions2025/5/1
- A Physics-Informed Machine Learning Framework for Safe and Optimal Control of Autonomous Systems2025/2/1
- DualGuard MPPI: Safe and Performant Optimal Control by Combining Sampling-Based MPC and Hamilton-Jacobi Reachability2025/2/1
- One Filter to Deploy Them All: Robust Safety for Quadrupedal Navigation in Unknown Environments2024/12/13
- One Filter to Deploy Them All: Robust Safety for Quadrupedal Navigation in Unknown Environments2024/12/1
- Enhancing Safety and Robustness of Vision-Based Controllers via Reachability Analysis2024/10/1
- Cooptimizing Safety and Performance with a Control-Constrained Formulation2024/9/1
- Updating Robot Safety Representations Online from Natural Language Feedback2024/9/1
- Gait Switching and Enhanced Stabilization of Walking Robots with Deep Learning-based Reachability: A Case Study on Two-link Walker2024/9/1
- System-Level Safety Monitoring and Recovery for Perception Failures in Autonomous Vehicles2024/9/1
- Stable-BC: Controlling Covariate Shift with Stable Behavior Cloning2024/8/1
- Parameterized Fast and Safe Tracking (FaSTrack) using Deepreach2024/4/1
- Exact Imposition of Safety Boundary Conditions in Neural Reachable Tubes2024/4/1
- SAFE-GIL: SAFEty Guided Imitation Learning for Robotic Systems2024/4/1
- Providing Safety Assurances for Systems with Unknown Dynamics2024/3/1
- Verification of Neural Reachable Tubes via Scenario Optimization and Conformal Prediction2023/12/1
- On Safety and Liveness Filtering Using Hamilton-Jacobi Reachability Analysis2023/12/1
- Hamilton-Jacobi Reachability Analysis for Hybrid Systems with Controlled and Forced Transitions2023/9/1
- Detecting and Mitigating System-Level Anomalies of Vision-Based Controllers2023/9/1
- Discovering Closed-Loop Failures of Vision-Based Controllers via Reachability Analysis2022/11/1
- Online Update of Safety Assurances Using Confidence-Based Predictions2022/10/1
- Parameter-Conditioned Reachable Sets for Updating Safety Assurances Online2022/9/1
- Generating Formal Safety Assurances for High-Dimensional Reachability2022/9/1
- Computation of Regions of Attraction for Hybrid Limit Cycles Using Reachability: An Application to Walking Robots2022/1/1
- FaSTrack: a Modular Framework for Real-Time Motion Planning and Guaranteed Safe Tracking2021/2/1
- DeepReach: A Deep Learning Approach to High-Dimensional Reachability2020/11/1
- Visual Navigation Among Humans with Optimal Control as a Supervisor2020/3/1
- Generating Robust Supervision for Learning-Based Visual Navigation Using Hamilton-Jacobi Reachability2019/12/1
- A Hamilton-Jacobi Reachability-Based Framework for Predicting and Analyzing Human Motion for Safe Planning2019/10/1
- An Efficient Reachability-Based Framework for Provably Safe Autonomous Navigation in Unknown Environments2019/5/1
- Combining Optimal Control and Learning for Visual Navigation in Novel Environments2019/3/1
- A New Simulation Metric to Determine Safe Environments and Controllers for Systems with Unknown Dynamics2019/2/1
- Context-Specific Validation of Data-Driven Models2018/2/1
- MBMF: Model-Based Priors for Model-Free Reinforcement Learning2017/9/1
- FaSTrack: a Modular Framework for Fast and Guaranteed Safe Motion Planning2017/3/1
- Learning Quadrotor Dynamics Using Neural Network for Flight Control2016/10/1