{"total":61,"rows":[{"id":"2204.01691","title":"Do As I Can, Not As I Say: Grounding Language in Robotic Affordances","created":"2022-04-04","cited_by_count":2348,"area":null},{"id":"2106.14405","title":"Habitat 2.0: Training Home Assistants to Rearrange their Habitat","created":"2021-06-28","cited_by_count":511,"area":null},{"id":"2311.17842","title":"Look Before You Leap: Unveiling the Power of GPT-4V in Robotic Vision-Language Planning","created":"2023-11-29","cited_by_count":161,"area":null},{"id":"2306.11565","title":"HomeRobot: Open-Vocabulary Mobile Manipulation","created":"2023-06-20","cited_by_count":106,"area":null},{"id":"2104.11213","title":"ManipulaTHOR: A Framework for Visual Object Manipulation","created":"2021-04-22","cited_by_count":102,"area":null},{"id":"2209.10342","title":"Partially Observable Markov Decision Processes in Robotics: A Survey","created":"2022-09-21","cited_by_count":86,"area":null},{"id":"2303.00855","title":"Grounded Decoding: Guiding Text Generation with Grounded Models for Embodied Agents","created":"2023-03-01","cited_by_count":67,"area":"agents"},{"id":"2305.16309","title":"Imitating Task and Motion Planning with Visuomotor Transformers","created":"2023-05-25","cited_by_count":66,"area":"offlinerl"},{"id":"2405.01534","title":"Plan-Seq-Learn: Language Model Guided RL for Solving Long Horizon Robotics Tasks","created":"2024-05-02","cited_by_count":52,"area":null},{"id":"2203.09634","title":"Predicate Invention for Bilevel Planning","created":"2022-03-17","cited_by_count":49,"area":null},{"id":"2105.14074","title":"Learning Neuro-Symbolic Relational Transition Models for Bilevel Planning","created":"2021-05-28","cited_by_count":43,"area":null},{"id":"2202.00732","title":"IFOR: Iterative Flow Minimization for Robotic Object Rearrangement","created":"2022-02-01","cited_by_count":42,"area":null},{"id":"2108.04145","title":"Long-Horizon Manipulation of Unknown Objects via Task and Motion Planning with Estimated Affordances","created":"2021-08-09","cited_by_count":40,"area":null},{"id":"2404.10220","title":"Closed-Loop Open-Vocabulary Mobile Manipulation with GPT-4V","created":"2024-04-16","cited_by_count":40,"area":null},{"id":"2106.01352","title":"NeRP: Neural Rearrangement Planning for Unknown Objects","created":"2021-06-02","cited_by_count":34,"area":null},{"id":"2312.14950","title":"TypeFly: Flying Drones with Large Language Model","created":"2023-12-08","cited_by_count":23,"area":null},{"id":"2402.15025","title":"Practice Makes Perfect: Planning to Learn Skill Parameter Policies","created":"2024-02-22","cited_by_count":23,"area":null},{"id":"2306.13196","title":"DiMSam: Diffusion Models as Samplers for Task and Motion Planning under Partial Observability","created":"2023-06-22","cited_by_count":22,"area":"diffusion"},{"id":"2309.15459","title":"GAMMA: Graspability-Aware Mobile MAnipulation Policy Learning based on Online Grasping Pose Fusion","created":"2023-09-27","cited_by_count":22,"area":null},{"id":"2410.22332","title":"Local Policies Enable Zero-shot Long-horizon Manipulation","created":"2024-10-29","cited_by_count":22,"area":null},{"id":"2210.04964","title":"Generating Executable Action Plans with Environmentally-Aware Language Models","created":"2022-10-10","cited_by_count":21,"area":null},{"id":"2304.09302","title":"CabiNet: Scaling Neural Collision Detection for Object Rearrangement with Procedural Scene Generation","created":"2023-04-18","cited_by_count":18,"area":null},{"id":"2207.04364","title":"Sequential Manipulation Planning on Scene Graph","created":"2022-07-10","cited_by_count":17,"area":null},{"id":"2403.10454","title":"Partially Observable Task and Motion Planning with Uncertainty and Risk Awareness","created":"2024-03-15","cited_by_count":17,"area":null},{"id":"2505.21981","title":"Learning Compositional Behaviors from Demonstration and Language","created":"2025-05-28","cited_by_count":15,"area":"offlinerl"},{"id":"2111.13144","title":"Learning to Search in Task and Motion Planning with Streams","created":"2021-11-25","cited_by_count":10,"area":null},{"id":"2210.01287","title":"Robot Task Planning and Situation Handling in Open Worlds","created":"2022-10-04","cited_by_count":10,"area":null},{"id":"2103.14283","title":"OmniHang: Learning to Hang Arbitrary Objects using Contact Point Correspondences and Neural Collision Estimation","created":"2021-03-26","cited_by_count":9,"area":null},{"id":"2411.08253","title":"Open-World Task and Motion Planning via Vision-Language Model Generated Constraints","created":"2024-11-13","cited_by_count":9,"area":"mllm"},{"id":"2203.04605","title":"Representation, learning, and planning algorithms for geometric task and motion planning","created":"2022-03-09","cited_by_count":8,"area":null},{"id":"2104.04696","title":"MPTP: Motion-Planning-aware Task Planning for Navigation in Belief Space","created":"2021-04-10","cited_by_count":7,"area":null},{"id":"2509.21983","title":"Hybrid Diffusion for Simultaneous Symbolic and Continuous Planning","created":"2025-09-26","cited_by_count":7,"area":null},{"id":"2406.03641","title":"Task and Motion Planning for Execution in the Real","created":"2024-06-05","cited_by_count":6,"area":null},{"id":"2309.15278","title":"Out of Sight, Still in Mind: Reasoning and Planning about Unobserved Objects with Video Tracking Enabled Memory Models","created":"2023-09-26","cited_by_count":5,"area":null},{"id":"2402.15402","title":"Grasp, See, and Place: Efficient Unknown Object Rearrangement with Policy Structure Prior","created":"2024-02-23","cited_by_count":5,"area":null},{"id":"2310.01775","title":"STAMP: Differentiable Task and Motion Planning via Stein Variational Gradient Descent","created":"2023-10-03","cited_by_count":4,"area":"lr"},{"id":"2404.15194","title":"Closed Loop Interactive Embodied Reasoning for Robot Manipulation","created":"2024-04-23","cited_by_count":4,"area":null},{"id":"2501.13338","title":"CuriousBot: Interactive Mobile Exploration via Actionable 3D Relational Object Graph","created":"2025-01-23","cited_by_count":4,"area":null},{"id":"2506.07062","title":"Prime the search: Using large language models for guiding geometric task and motion planning by warm-starting tree search","created":"2025-06-08","cited_by_count":4,"area":null},{"id":"2510.00182","title":"A Systematic Study of Large Language Models for Task and Motion Planning With PDDLStream","created":"2025-09-30","cited_by_count":4,"area":null},{"id":"2305.06004","title":"Safe motion planning with environment uncertainty","created":"2023-05-10","cited_by_count":3,"area":null},{"id":"2410.18964","title":"Learning to Look: Seeking Information for Decision Making via Policy Factorization","created":"2024-10-24","cited_by_count":3,"area":null},{"id":"2501.17104","title":"COS(M+O)S: Curiosity and RL-Enhanced MCTS for Exploring Story Space via Language Models","created":"2025-01-28","cited_by_count":3,"area":"lr"},{"id":"2104.01549","title":"A Task-Motion Planning Framework Using Iteratively Deepened AND/OR Graph Networks","created":"2021-04-04","cited_by_count":2,"area":null},{"id":"2303.04327","title":"Using Memory-Based Learning to Solve Tasks with State-Action Constraints","created":"2023-03-08","cited_by_count":2,"area":null},{"id":"2411.18201","title":"Learning for Long-Horizon Planning via Neuro-Symbolic Abductive Imitation","created":"2024-11-27","cited_by_count":2,"area":null},{"id":"2501.00953","title":"Prior Lessons of Incremental Dialogue and Robot Action Management for the Age of Language Models","created":"2025-01-01","cited_by_count":2,"area":null},{"id":"2503.08604","title":"EMMOE: A Comprehensive Benchmark for Embodied Mobile Manipulation in Open Environments","created":"2025-03-11","cited_by_count":2,"area":null},{"id":"2603.03704","title":"Large-Language-Model-Guided State Estimation for Partially Observable Task and Motion Planning","created":"2026-03-04","cited_by_count":2,"area":null},{"id":"2210.14055","title":"Policy-Guided Lazy Search with Feedback for Task and Motion Planning","created":"2022-10-25","cited_by_count":1,"area":null},{"id":"2412.01348","title":"Hierarchical Object-Oriented POMDP Planning for Object Rearrangement","created":"2024-12-02","cited_by_count":1,"area":null},{"id":"2601.18930","title":"Toward Learning POMDPs Beyond Full-Rank Actions and State Observability","created":"2026-01-26","cited_by_count":1,"area":null},{"id":"2602.19260","title":"The Price Is Not Right: Neuro-Symbolic Methods Outperform VLAs on Structured Long-Horizon Manipulation Tasks with Significantly Lower Energy Consumption","created":"2026-02-22","cited_by_count":1,"area":"vla"},{"id":"2609.19315","title":"GAVEL: Graph World Models for Verified and Efficient Long-Horizon LLM Task Planning","created":"2026-09-16","cited_by_count":1,"area":"wm"},{"id":"2108.12537","title":"An Anytime Hierarchical Approach for Stochastic Task and Motion Planning","created":"2021-08-28","cited_by_count":0,"area":null},{"id":"2504.17901","title":"Task and Skill Planning: Hierarchical Robot Planning with Black-Box Skills","created":"2025-04-24","cited_by_count":0,"area":null},{"id":"2504.21596","title":"Leveraging Pre-trained Large Language Models with Refined Prompting for Online Task and Motion Planning","created":"2025-04-30","cited_by_count":0,"area":null},{"id":"2509.00317","title":"A Framework for Task and Motion Planning based on Expanding AND/OR Graphs","created":"2025-08-30","cited_by_count":0,"area":null},{"id":"2510.14065","title":"Optimistic Reinforcement Learning-Based Skill Insertions for Task and Motion Planning","created":"2025-10-15","cited_by_count":0,"area":"deeprl"},{"id":"2604.03759","title":"Build on Priors: Vision--Language--Guided Neuro-Symbolic Imitation Learning for Data-Efficient Real-World Robot Manipulation","created":"2026-04-04","cited_by_count":0,"area":"offlinerl"},{"id":"2608.20084","title":"Evidence-Gated Task and Motion Planning with Vision-Language Models","created":"2026-08-20","cited_by_count":0,"area":"mllm"}],"next_cursor":null}