Object and Contact Point Tracking in Demonstrations Using 3D Gaussian Splatting

Autor:	Büttner, Michael, Francis, Jonathan, Rhodin, Helge, Melnik, Andrew
Rok vydání:	2024
Předmět:	Computer Science - Computer Vision and Pattern Recognition Computer Science - Robotics
Druh dokumentu:	Working Paper
Popis:	This paper introduces a method to enhance Interactive Imitation Learning (IIL) by extracting touch interaction points and tracking object movement from video demonstrations. The approach extends current IIL systems by providing robots with detailed knowledge of both where and how to interact with objects, particularly complex articulated ones like doors and drawers. By leveraging cutting-edge techniques such as 3D Gaussian Splatting and FoundationPose for tracking, this method allows robots to better understand and manipulate objects in dynamic environments. The research lays the foundation for more effective task learning and execution in autonomous robotic systems. Comment: CoRL 2024, Workshop on Lifelong Learning for Home Robots, Munich, Germany
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2411.03555 Zobrazit plný text záznamu View this record from Arxiv