Control techniques for safe, ergonomic, and efficient human-robot collaboration in the digital industry: A survey

S Proia, R Carli, G Cavone… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
The fourth industrial revolution, also known as Industry 4.0, is resha** the way individuals
live and work while providing a substantial influence on the manufacturing scenario. The key …

Efficient multitask learning with an embodied predictive model for door opening and entry with whole-body control

H Ito, K Yamamoto, H Mori, T Ogata - Science Robotics, 2022 - science.org
Robots need robust models to effectively perform tasks that humans do on a daily basis.
These models often require substantial developmental costs to maintain because they need …

Neural network-based adaptive controller design for robotic manipulator subject to varying loads and unknown dead-zone

X Zhao, Z Liu, Q Zhu - Neurocomputing, 2023 - Elsevier
In this article, aiming at handling the trajectory tracking issue of industrial manipulator
system (IMS) with modeling uncertainty, varying loads (VL) and unknown dead-zone …

In-air knotting of rope using dual-arm robot based on deep learning

K Suzuki, M Kanamura, Y Suga… - 2021 IEEE/RSJ …, 2021 - ieeexplore.ieee.org
In this study, we report the successful execution of in-air knotting of rope using a dual-arm
two-finger robot based on deep learning. Owing to its flexibility, the state of the rope was in …

Deep predictive learning: Motion learning concept inspired by cognitive robotics

K Suzuki, H Ito, T Yamada, K Kase, T Ogata - ar** for series of tasks in atypical environment: Robotic system with reliable program-based and flexible learning-based approaches
H Ito, S Nakamura - ROBOMECH Journal, 2022 - Springer
We propose a novel robotic system that combines both a reliable programming-based
approach and a highly generalizable learning-based approach. How to design and …