4 papers
Interpretable Robotic Friction Learning via Symbolic Regression
Philipp Scholl, Alexander Dietrich, Sebastian Wolf +4
Accurately modeling the friction torque in robotic joints has long been challenging due to the request for a robust mathematical description. Traditional model-based approaches are…
Stronger Than You Think: Benchmarking Weak Supervision on Realistic Tasks
Tianyi Zhang, Linrong Cai, Jeffrey Li +4
Weak supervision (WS) is a popular approach for label-efficient learning, leveraging diverse sources of noisy but inexpensive weak labels to automatically annotate training data. D…
Online Multi-Contact Feedback Model Predictive Control for Interactive Robotic Tasks
Seo Wook Han, Maged Iskandar, Jinoh Lee +1
In this paper, we propose a model predictive control (MPC) that accomplishes interactive robotic tasks, in which multiple contacts may occur at unknown locations. To address such s…
Learning-based adaption of robotic friction models
Philipp Scholl, Maged Iskandar, Sebastian Wolf +5
In the Fourth Industrial Revolution, wherein artificial intelligence and the automation of machines occupy a central role, the deployment of robots is indispensable. However, the m…