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Task and Motion Planning

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Showing 51–75 of 86 papers

TitleStatusHype
Representation, learning, and planning algorithms for geometric task and motion planning—0
RH20T: A Comprehensive Robotic Dataset for Learning Diverse Skills in One-Shot—0
Risk-aware Integrated Task and Motion Planning for Versatile Snake Robots under Localization Failures—0
Sequence-Based Plan Feasibility Prediction for Efficient Task and Motion Planning—0
Socially intelligent task and motion planning for human-robot interaction—0
SPIRE: Synergistic Planning, Imitation, and Reinforcement Learning for Long-Horizon Manipulation—0
STAMP: Differentiable Task and Motion Planning via Stein Variational Gradient Descent—0
Task Allocation for Multi-Robot Task and Motion Planning: a case for Object Picking in Cluttered Workspaces—0
Task and Motion Planning for Execution in the Real—0
RobKiNet: Robotic Kinematics Informed Neural Network for Optimal Robot Configuration Prediction—0
Towards Robust and Secure Embodied AI: A Survey on Vulnerabilities and Attacks—0
Understanding Physical Properties of Unseen Deformable Objects by Leveraging Large Language Models and Robot Actions—0
Unified Task and Motion Planning using Object-centric Abstractions of Motion Constraints—0
VLM See, Robot Do: Human Demo Video to Robot Action Plan via Vision Language Model—0
Zero-shot Robotic Manipulation with Language-guided Instruction and Formal Task Planning—0
Multi-step manipulation task and motion planning guided by video demonstration—0
Accelerated Labeling of Discrete Abstractions for Autonomous Driving Subject to LTL Specifications—0
Accelerating Integrated Task and Motion Planning with Neural Feasibility Checking—0
Admissible Abstractions for Near-optimal Task and Motion Planning—0
A Long Horizon Planning Framework for Manipulating Rigid Pointcloud Objects—0
A Meta-Engine Framework for Interleaved Task and Motion Planning using Topological Refinements—0
An Anytime Algorithm for Task and Motion MDPs—0
Anytime Integrated Task and Motion Policies for Stochastic Environments—0
An Anytime Hierarchical Approach for Stochastic Task and Motion Planning—0
A Survey of Optimization-based Task and Motion Planning: From Classical To Learning Approaches—0
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