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arXiv · 2312.13906

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

Benjamin Alt·Minh Dang Nguyen·Andreas Hermann·Darko Katic·Rainer Jäkel·Rüdiger Dillmann·Eric Sax
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Abstract

The use of autonomous robots for assistance tasks in hospitals has the potential to free up qualified staff and im-prove patient care. However, the ubiquity of deformable and transparent objects in hospital settings poses signif-icant 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 ma-nipulation 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 arm.

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Benjamin Alt, Minh Dang Nguyen, Andreas Hermann, Darko Katic, Rainer Jäkel, Rüdiger Dillmann, Eric Sax. 2023-12-21. EfficientPPS: Part-aware Panoptic Segmentation of Transparent Objects for Robotic Manipulation. https://arxiv.org/abs/2312.13906

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