EfficientPPS: Part-aware Panoptic Segmentation of Transparent Objects for Robotic Manipulation

作     者：Alt, Benjamin Nguyen, Minh Dang Hermann, Andreas Katic, Darko Jäkel, Rainer Dillmann, Rüdiger Sax, Eric 

作者机构：ArtiMinds Robotics Karlsruhe Germany Intelligent Systems and Production Engineering Forschungszentrum Informatik Karlsruhe Germany  Karlsruhe Institute of Technology Germany 

出 版 物：《arXiv》 (arXiv)

年 卷 期：2023年

核心收录：

主　　题：Hospitals 

摘      要：The use of autonomous robots for assistance tasks in hospitals has the potential to free up qualified staff and improve patient care. However, the ubiquity of deformable and transparent objects in hospital settings poses significant challenges to vision-based perception systems. We present EfficientPPS, a neural architecture for part-aware panoptic segmentation that provides robots with semantically rich visual information for grasping and manipulation tasks. We also present an unsupervised data collection and labelling method to reduce the need for human involvement in the training process. EfficientPPS is evaluated on a dataset containing real-world hospital objects and demonstrated to be robust and efficient in grasping transparent transfusion bags with a collaborative robot *** Codes 68T45 © 2023, CC BY-SA.