Teat Pose Estimation via RGBD Segmentation for Automated Milking

Autor:	Borla, Nicolas, Kuster, Fabian, Langenegger, Jonas, Ribera, Juan, Honegger, Marcel, Toffetti, Giovanni
Rok vydání:	2021
Předmět:	Computer Science - Robotics
Druh dokumentu:	Working Paper
Popis:	We present initial results in the development of a novel robot using RGBD cameras, image segmentation, and a simple teat pose estimation algorithm for automated milking. We relate on the analysis of the accuracy of different commercial RGBD cameras in realistic conditions. Although preliminary, our initial implementation shows that 2D image segmentation combined with point cloud processing can achieve repeatable millimeter-scale precision in estimating (synthetic) teat tip positions and cup attachment approach. The solution is also applicable in a cloud robotics setup, with GPU-based segmentation executed on an edge device or cloud. Comment: Accepted for publication at the "Task-Informed Grasping: Agri-Food manipulation" (TIG-III) Workshop at ICRA 2021
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2105.09843 Zobrazit plný text záznamu View this record from Arxiv