FOGL: Federated Object Grasping Learning
Seok–Kyu Kang,Changhyun Choi,Seok–Kyu Kang,Changhyun Choi
Federated learning is a promising technique for training global models in a data-decentralized environment. In this paper, we propose a federated learning approach for robotic object grasping. The main challenge is that the data collected by multiple robots deployed in different environments tends to form heterogeneous data distributions (i.e., non-IID) and that the existing federated learning met...
