Tomás Lozano-Pérez
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
- TiPToP: A Modular Open-Vocabulary Robot Manipulation System That Plans2026/3/1
- 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
- From Pixels to Predicates: Learning Symbolic World Models via Pretrained Vision-Language Models2025/1/1
- One-Shot Manipulation Strategy Learning by Making Contact Analogies2024/11/1
- Open-World Task and Motion Planning via Vision-Language Model Generated Constraints2024/11/1
- Differentiable GPU-Parallelized Task and Motion Planning2024/11/1
- Keypoint Abstraction using Large Models for Object-Relative Imitation Learning2024/10/1
- SceneComplete: Open-World 3D Scene Completion in Cluttered Real World Environments for Robot Manipulation2024/10/1
- Combining Planning and Diffusion for Mobility with Unknown Dynamics2024/10/1
- Guiding Long-Horizon Task and Motion Planning with Vision Language Models2024/10/1
- Learning to Bridge the Gap: Efficient Novelty Recovery with Planning and Reinforcement Learning2024/9/1
- Embodied Uncertainty-Aware Object Segmentation2024/8/1
- 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
- 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
- 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
- Sequence-Based Plan Feasibility Prediction for Efficient Task and Motion Planning2022/11/1
- Learning Efficient Abstract Planning Models that Choose What to Predict2022/8/1
- Robust Planning for Multi-stage Forceful Manipulation2022/8/1
- Fully Persistent Spatial Data Structures for Efficient Queries in Path-Dependent Motion Planning Applications2022/6/1
- 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
- Long-Horizon Manipulation of Unknown Objects via Task and Motion Planning with Estimated Affordances2021/8/1
- Active Learning of Abstract Plan Feasibility2021/7/1
- Learning When to Quit: Meta-Reasoning for Motion Planning2021/3/1
- Planning for Multi-stage Forceful Manipulation2021/1/1
- Integrated Task and Motion Planning2020/10/1
- Visual Prediction of Priors for Articulated Object Interaction2020/6/1
- Learning compositional models of robot skills for task and motion planning2020/6/1
- Scalable and Probabilistically Complete Planning for Robotic Spatial Extrusion2020/2/1
- Online Replanning in Belief Space for Partially Observable Task and Motion Problems2019/11/1
- Learning Compact Models for Planning with Exogenous Processes2019/9/1
- Look before you sweep: Visibility-aware motion planning2019/1/1
- Learning Quickly to Plan Quickly Using Modular Meta-Learning2018/9/1
- Modular meta-learning2018/6/1
- 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
- Provably Safe Robot Navigation with Obstacle Uncertainty2017/5/1
- Focused Model-Learning and Planning for Non-Gaussian Continuous State-Action Systems2016/7/1
- Object-based World Modeling in Semi-Static Environments with Dependent Dirichlet-Process Mixtures2015/12/1