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.
Robotics14 thg 6
Navigation World Action Model for Goal-Conditioned Visual Navigation

Robotics14 thg 6
SPARC: Reliable Spatial Annotations from Robot Demonstrations at Scale

AI14 thg 6
Heterogeneous LiDAR Early Fusion and Learned Re-Ranking for Robust Long-Term Place Recognition

AI13 thg 6
MaskWAM Teaches Robots to Predict What Matters for Better Manipulation

AI13 thg 6
LabVLA Brings Vision-Language-Action Models to Lab Automation

Robotics13 thg 6
MCR-Bionic Hand: How Anatomical Structure Unlocks Dexterous Robot Manipulation

Robotics12 thg 6
Weaver: A Fast and Scalable World Model for Robotic Manipulation

Robotics12 thg 6
Flow Reversal Steering Makes Robot Generalists Better at Following High-Level Guidance

AI12 thg 6
Mana: A New System for Dexterous Robot Manipulation of Articulated Tools

AI11 thg 6
When and Where Should You Allocate Test-Time Compute in Embodied Planners?

Robotics11 thg 6
World Pilot Gives Vision-Language-Action Robots a World-Action Model Boost

AI11 thg 6
New Method Gives Cheap Robot Arms Force Feedback Without Extra Sensors

Humanoid10 thg 6
Embodied mmWave Radar on Humanoid Robots Enables 24/7 Fall Detection

Robotics10 thg 6
Bimanual Joining System Lets Wheelchair Robots Call for Backup

Robotics10 thg 6
TacForeSight Predicts Tactile Feedback From Force Data for Better Robot Handling

AI9 thg 6
AHA-WAM: Asynchronous World-Action Model for Faster, Smarter Robot Manipulation

Robotics9 thg 6
How Robots Turn Actions Into Motion and Contact Images for Better World Models

Robotics9 thg 6
MemoryVLA++ Equips Robots with Memory and Imagination for Complex Tasks

AI8 thg 6
