Leslie Pack Kaelbling
収録論文 62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
- Which Reconstruction Model Should a Robot Use? Routing Image-to-3D Models for Cost-Aware Robotic Manipulation2026/3/1
- TiPToP: A Modular Open-Vocabulary Robot Manipulation System That Plans2026/3/1
- "Set It Up": Functional Object Arrangement with Compositional Generative Models (Journal Version)2025/8/1
- Rational Inverse Reasoning: Few-Shot Imitation by Inferring Intent through Planning2025/8/1
- Streaming Flow Policy: Simplifying diffusion/flow-matching policies by treating action trajectories as flow trajectories2025/5/1
- Seeing is Believing: Belief-Space Planning with Foundation Models as Uncertainty Estimators2025/4/1
- Flow-based Domain Randomization for Learning and Sequencing Robotic Skills2025/2/1
- From Pixels to Predicates: Learning Symbolic World Models via Pretrained Vision-Language Models2025/1/1
- Open-World Task and Motion Planning via Vision-Language Model Generated Constraints2024/11/1
- One-Shot Manipulation Strategy Learning by Making Contact Analogies2024/11/1
- Differentiable GPU-Parallelized Task and Motion Planning2024/11/1
- Combining Planning and Diffusion for Mobility with Unknown Dynamics2024/10/1
- SceneComplete: Open-World 3D Scene Completion in Cluttered Real World Environments for Robot Manipulation2024/10/1
- Guiding Long-Horizon Task and Motion Planning with Vision Language Models2024/10/1
- Keypoint Abstraction using Large Models for Object-Relative Imitation Learning2024/10/1
- Embodied Uncertainty-Aware Object Segmentation2024/8/1
- GCS*: Forward Heuristic Search on Implicit Graphs of Convex Sets2024/7/1
- Towards Practical Finite Sample Bounds for Motion Planning in TAMP2024/7/1
- Trust the PRoC3S: Solving Long-Horizon Robotics Problems with LLMs and Constraint Satisfaction2024/6/1
- "Set It Up!": Functional Object Arrangement with Compositional Generative Models2024/5/1
- Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness2024/3/1
- Practice Makes Perfect: Planning to Learn Skill Parameter Policies2024/2/1
- Learning Reusable Manipulation Strategies2023/11/1
- Compositional Diffusion-Based Continuous Constraint Solvers2023/9/1
- Distilled Feature Fields Enable Few-Shot Language-Guided Manipulation2023/8/1
- Embodied Lifelong Learning for Task and Motion Planning2023/7/1
- DiMSam: Diffusion Models as Samplers for Task and Motion Planning under Partial Observability2023/6/1
- PDSketch: Integrated Planning Domain Programming and Learning2023/3/1
- Visibility-Aware Navigation Among Movable Obstacles2022/12/1
- SE(3)-Equivariant Relational Rearrangement with Neural Descriptor Fields2022/11/1
- Learning Efficient Abstract Planning Models that Choose What to Predict2022/8/1
- Learning Neuro-Symbolic Skills for Bilevel Planning2022/6/1
- Fully Persistent Spatial Data Structures for Efficient Queries in Path-Dependent Motion Planning Applications2022/6/1
- Predicate Invention for Bilevel Planning2022/3/1
- Representation, learning, and planning algorithms for geometric task and motion planning2022/3/1
- Specifying and achieving goals in open uncertain robot-manipulation domains2021/12/1
- Discovering State and Action Abstractions for Generalized Task and Motion Planning2021/9/1
- Long-Horizon Manipulation of Unknown Objects via Task and Motion Planning with Estimated Affordances2021/8/1
- Learning Neuro-Symbolic Relational Transition Models for Bilevel Planning2021/5/1
- Learning When to Quit: Meta-Reasoning for Motion Planning2021/3/1
- Learning Symbolic Operators for Task and Motion Planning2021/3/1
- Integrated Task and Motion Planning2020/10/1
- CAMPs: Learning Context-Specific Abstractions for Efficient Planning in Factored MDPs2020/7/1
- Visual Prediction of Priors for Articulated Object Interaction2020/6/1
- Learning compositional models of robot skills for task and motion planning2020/6/1
- Online Replanning in Belief Space for Partially Observable Task and Motion Problems2019/11/1
- Differentiable Algorithm Networks for Composable Robot Learning2019/5/1
- Look before you sweep: Visibility-aware motion planning2019/1/1
- Learning sparse relational transition models2018/10/1
- Learning Quickly to Plan Quickly Using Modular Meta-Learning2018/9/1
- Learning to guide task and motion planning using score-space representation2018/7/1
- Learning What Information to Give in Partially Observed Domains2018/5/1
- Active model learning and diverse action sampling for task and motion planning2018/3/1
- Integrating Human-Provided Information Into Belief State Representation Using Dynamic Factorization2018/3/1
- PDDLStream: Integrating Symbolic Planners and Blackbox Samplers via Optimistic Adaptive Planning2018/2/1
- Sampling-Based Methods for Factored Task and Motion Planning2018/1/1
- Guiding the search in continuous state-action spaces by learning an action sampling distribution from off-target samples2017/11/1
- Provably Safe Robot Navigation with Obstacle Uncertainty2017/5/1
- FFRob: Leveraging Symbolic Planning for Efficient Task and Motion Planning2016/8/1
- Focused Model-Learning and Planning for Non-Gaussian Continuous State-Action Systems2016/7/1
- Backward-Forward Search for Manipulation Planning2016/4/1
- Object-based World Modeling in Semi-Static Environments with Dependent Dirichlet-Process Mixtures2015/12/1