Nghiên cứu Papers
Bản tóm tắt dễ hiểu về các nghiên cứu robot mới nhất — robot hình người, robot bốn chân, tự động hóa công nghiệp và AI.
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ARC: Adaptive Robust Estimation Handles Outliers and Unknown Noise in Real-Time Localization

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Slow Brain, Fast Planner: Keeping Robots Safe When AI Vision Takes Its Time

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GroundControl: Anticipating Navigation Failures in Vision-Language Agents Using Trajectory-Consistent Uncertainty

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Fast Human Attention Prediction Enables Real-Time Fixation-Guided Drone Navigation

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New Motion Planning Algorithms Make Continuum Robots More Resilient

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New Attention Mechanism Treats Robot Poses as Group Elements, Boosts Performance

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Generating Task-Specific Robot Hands from Human Fingertip Demonstrations

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MemoryWAM: Persistent Memory Makes Robot Action Models Faster and Smarter

AI18 thg 6
New Algorithm UBP2 Uses Uncertainty to Learn Robot Rewards from Preferences

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Do as I Do: Turning Everyday Human Videos Into Dexterous Robot Data

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Zero-Shot Long-Horizon Dexterous Manipulation with Multi-View 3D Grounded VLM Reasoning

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EBench: A New Benchmark Diagnoses Mobile Manipulation Robots' Core Capabilities
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MOCHI Cleans Up Noisy Multi-Human Object Interaction Data
AI17 thg 6
Visual Verifier Helps Robots Improve Their Own Policy Without Retraining

AI16 thg 6
Geometric Action Model Unifies Geometry and Action Prediction for Robot Learning

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Human Universal Grasping: A Model That Learns Diverse Natural Grasps

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T-Rex: Tactile-Reactive Dexterous Manipulation Using Robot Hands

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Whole-Body Impedance MPC Lets Legged Robots Safely Handle Human Pushes

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