most citedTeam O2AS at the World Robot Summit 2018: An Approach to Robotic Kitting and Assembly Tasks using General Purpose Grippers and Tools

21 citations

5 papers

cs.LG20202 cited

Adaptive Distillation for Decentralized Learning from Heterogeneous Clients

Jiaxin Ma, Ryo Yonetani, Zahid Iqbal

This paper addresses the problem of decentralized learning to achieve a high-performance global model by asking a group of clients to share local models pre-trained with their own…

cs.RO202021 cited

Team O2AS at the World Robot Summit 2018: An Approach to Robotic Kitting and Assembly Tasks using General Purpose Grippers and Tools

Felix von Drigalski, Chisato Nakashima, Yoshiya Shibata +12

We propose a versatile robotic system for kitting and assembly tasks which uses no jigs or commercial tool changers. Instead of specialized end effectors, it uses its two-finger gr…

cs.CV20201 cited

Partially-Shared Variational Auto-encoders for Unsupervised Domain Adaptation with Target Shift

Ryuhei Takahashi, Atsushi Hashimoto, Motoharu Sonogashira +1

This paper proposes a novel approach for unsupervised domain adaptation (UDA) with target shift. Target shift is a problem of mismatch in label distribution between source and targ…

cs.CV20193 cited

Crowd Density Forecasting by Modeling Patch-based Dynamics

Hiroaki Minoura, Ryo Yonetani, Mai Nishimura +1

Forecasting human activities observed in videos is a long-standing challenge in computer vision, which leads to various real-world applications such as mobile robots, autonomous dr…

cs.RO20196 cited

Robots Assembling Machines: Learning from the World Robot Summit 2018 Assembly Challenge

Felix von Drigalski, Christian Schlette, Martin Rudorfer +5

The Industrial Assembly Challenge at the World Robot Summit was held in 2018 to showcase the state-of-the-art of autonomous manufacturing systems. The challenge included various ta…