Ahmed H. Qureshi

Purdue University

収録論文 55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

• hint$^2$: 推論時時間論理ガイダンスのための階層的世界モデル
  操作/時間論理/世界モデル2026/8/13

  ロボットの操作ポリシーを線形時間論理(LTL)で表される複雑な指示に従わせるため、階層的世界モデルを用いて推論時に高レベルと低レベルの2つのガイダンスを生成する手法を提案した。

• NeHMO: Neural Hamilton-Jacobi Reachability Learning for Decentralized Safe Multi-Arm Motion Planning
  2026/7/1
• Physics-informed Goal-Conditioned Reinforcement Learning under Hybrid Contact Dynamics
  2026/5/1
• Weakly-supervised Learning for Physics-informed Neural Motion Planning via Sparse Roadmap
  2026/4/1
• Graph-of-Constraints Model Predictive Control for Reactive Multi-agent Task and Motion Planning
  2026/3/1
• PPGuide: Steering Diffusion Policies with Performance Predictive Guidance
  2026/3/1
• Formal Methods in Robot Policy Learning and Verification: A Survey on Current Techniques and Future Directions
  2026/2/1
• Multi-Agent Monte Carlo Tree Search for Makespan-Efficient Object Rearrangement in Cluttered Spaces
  2026/2/1
• Goal Reaching with Eikonal-Constrained Hierarchical Quasimetric Reinforcement Learning
  2025/12/1
• Manifold-constrained Hamilton-Jacobi Reachability Learning for Decentralized Multi-Agent Motion Planning
  2025/11/1
• Automaton Constrained Q-Learning
  2025/10/1
• Online Hierarchical Policy Learning using Physics Priors for Robot Navigation in Unknown Environments
  2025/10/1
• Robust Point Cloud Reinforcement Learning via PCA-Based Canonicalization
  2025/10/1
• Physics-informed Neural Time Fields for Prehensile Object Manipulation
  2025/8/1
• Manip4Care: Robotic Manipulation of Human Limbs for Solving Assistive Tasks
  2025/8/1
• Multimodal Human-Intent Modeling for Contextual Robot-to-Human Handovers of Arbitrary Objects
  2025/8/1
• NeHMO: Neural Hamilton-Jacobi Reachability Learning for Decentralized Safe Multi-Arm Motion Planning
  2025/7/1
• Physics-informed Neural Motion Planning via Domain Decomposition in Large Environments
  2025/6/1
• Physics-Conditioned Grasping for Stable Tool Use
  2025/5/1
• Differentiable Composite Neural Signed Distance Fields for Robot Navigation in Dynamic Indoor Environments
  2025/2/1
• Implicit Physics-aware Policy for Dynamic Manipulation of Rigid Objects via Soft Body Tools
  2025/2/1
• Integrating Active Sensing and Rearrangement Planning for Efficient Object Retrieval from Unknown, Confined, Cluttered Environments
  2024/11/1
• Physics-informed Neural Mapping and Motion Planning in Unknown Environments
  2024/10/1
• Physics-informed Neural Motion Planning on Constraint Manifolds
  2024/3/1
• Neural Rearrangement Planning for Object Retrieval from Confined Spaces Perceivable by Robot's In-hand RGB-D Sensor
  2024/2/1
• Language-guided Active Sensing of Confined, Cluttered Environments via Object Rearrangement Planning
  2024/2/1
• Structural Concept Learning via Graph Attention for Multi-Level Rearrangement Planning
  2023/9/1
• DeRi-IGP: Learning to Manipulate Rigid Objects Using Deformable Objects via Iterative Grasp-Pull
  2023/9/1
• Zero-Shot Constrained Motion Planning Transformers Using Learned Sampling Dictionaries
  2023/9/1
• Efficient Q-Learning over Visit Frequency Maps for Multi-agent Exploration of Unknown Environments
  2023/7/1
• SIMMF: Semantics-aware Interactive Multiagent Motion Forecasting for Autonomous Vehicle Driving
  2023/6/1
• MANER: Multi-Agent Neural Rearrangement Planning of Objects in Cluttered Environments
  2023/6/1
• Progressive Learning for Physics-informed Neural Motion Planning
  2023/6/1
• Multi-Stage Monte Carlo Tree Search for Non-Monotone Object Rearrangement Planning in Narrow Confined Environments
  2023/5/1
• DeRi-Bot: Learning to Collaboratively Manipulate Rigid Objects via Deformable Objects
  2023/5/1
• Co-learning Planning and Control Policies Constrained by Differentiable Logic Specifications
  2023/3/1
• Control Transformer: Robot Navigation in Unknown Environments through PRM-Guided Return-Conditioned Sequence Modeling
  2022/11/1
• NTFields: Neural Time Fields for Physics-Informed Robot Motion Planning
  2022/10/1
• CoGrasp: 6-DoF Grasp Generation for Human-Robot Collaboration
  2022/10/1
• Robot Active Neural Sensing and Planning in Unknown Cluttered Environments
  2022/8/1
• Co-design of Embodied Neural Intelligence via Constrained Evolution
  2022/5/1
• Model-free Neural Lyapunov Control for Safe Robot Navigation
  2022/3/1
• Motion Planning Transformers: A Motion Planning Framework for Mobile Robots
  2021/6/1
• NeRP: Neural Rearrangement Planning for Unknown Objects
  2021/6/1
• MPC-MPNet: Model-Predictive Motion Planning Networks for Fast, Near-Optimal Planning under Kinodynamic Constraints
  2021/1/1
• Constrained Motion Planning Networks X
  2020/10/1
• Dynamically Constrained Motion Planning Networks for Non-Holonomic Robots
  2020/8/1
• Neural Manipulation Planning on Constraint Manifolds
  2020/8/1
• Motion Planning Networks: Bridging the Gap Between Learning-based and Classical Motion Planners
  2019/7/1
• Composing Task-Agnostic Policies with Deep Reinforcement Learning
  2019/5/1
• Neural Path Planning: Fixed Time, Near-Optimal Path Generation via Oracle Imitation
  2019/4/1
• Adversarial Imitation via Variational Inverse Reinforcement Learning
  2018/9/1
• Deeply Informed Neural Sampling for Robot Motion Planning
  2018/9/1
• Potentially Guided Bidirectionalized RRT* for Fast Optimal Path Planning in Cluttered Environments
  2018/7/1
• Motion Planning Networks
  2018/6/1