Скачать или смотреть HERO: Precise Humanoid Control for Novel Objects

In this AI Research Roundup episode, Alex discusses the paper: 'Learning Humanoid End-Effector Control for Open-Vocabulary Visual Loco-Manipulation' This research introduces HERO, a modular framework designed to help humanoid robots interact with unknown objects in real-world settings using natural language. The study tackles the precision gap where humanoid robots often struggle with accurate hand movements despite having advanced locomotion. By combining vision models like Grounding DINO 1.5 and SAM-3 with classical robotics, HERO enables robots to detect, segment, and grasp objects based on free-form text. The system achieves high precision by decoupling action planning from execution and using improved inverse kinematics for better tracking. This approach overcomes the limitations of imitation learning by allowing robots to generalize to new environments without massive datasets. Paper URL: https://arxiv.org/abs/2602.16705 #AI #MachineLearning #DeepLearning #HumanoidRobots #Robotics #ComputerVision #ObjectManipulation #HERO