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Meet HITL-TAMP: A New AI Approach to Teach Robots Complex Manipulation Skills Through a Hybrid Strategy of Automated Planning and Human Control

[ad_1] Teaching robots complicated manipulation skills through observation of human demonstrations has shown promising results. Providing extensive manipulation demonstrations is time-consuming and labor costly, making it challenging to scale up this paradigm to real-world long-horizon operations. However, not all facets of a task…

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Researchers from NVIDIA and UT Austin Introduced MimicGen: An Autonomous Data Generation System for Robotics

[ad_1] Training robots to perform various manipulation behaviors has been made possible by imitation learning from human demonstrations. One popular method involves having human operators teleoperate with robot arms through various control interfaces, producing multiple demonstrations of robots performing different manipulation tasks, and…

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This AI Paper from MIT Introduces a Novel Approach to Robotic Manipulation: Bridging the 2D-to-3D Gap with Distilled Feature Fields and Vision-Language Models

[ad_1] A team of researchers from MIT and the Institute of AI and Fundamental Interactions (IAIFI) has introduced a groundbreaking framework for robotic manipulation, addressing the challenge of enabling robots to understand and manipulate objects in unpredictable and cluttered environments. The problem at…

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Meet GO To Any Thing (GOAT): A Universal Navigation System that can Find Any Object Specified in Any Way- as an Image, Language, or a Category- in Completely Unseen Environments

[ad_1] A team of researchers from the University of Illinois Urbana-Champaign, Carnegie Mellon University, Georgia Institute of Technology, University of California Berkeley, Meta AI Research, and Mistral AI has developed a universal navigation system called GO To Any Thing (GOAT). This system is…

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