Toward next-generation learned robot manipulation

J Cui, J Trinkle - Science robotics, 2021 - science.org
The ever-changing nature of human environments presents great challenges to robot
manipulation. Objects that robots must manipulate vary in shape, weight, and configuration …

Human–robot interaction review and challenges on task planning and programming

P Tsarouchi, S Makris… - International Journal of …, 2016 - Taylor & Francis
The wide interest of research and industry in the human–robot interaction (HRI) related
topics is proportional to the increased productivity and flexibility of the production lines, as it …

A deep learning framework for assessing physical rehabilitation exercises

Y Liao, A Vakanski, M **an - IEEE Transactions on Neural …, 2020 - ieeexplore.ieee.org
Computer-aided assessment of physical rehabilitation entails evaluation of patient
performance in completing prescribed rehabilitation exercises, based on processing …

Facilitating human–robot collaborative tasks by teaching-learning-collaboration from human demonstrations

W Wang, R Li, Y Chen, ZM Diekel… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Collaborative robots are widely employed in strict hybrid assembly tasks involved in
intelligent manufacturing. In this paper, we develop a teaching-learning-collaboration (TLC) …

[HTML][HTML] Multi-LeapMotion sensor based demonstration for robotic refine tabletop object manipulation task

H **, Q Chen, Z Chen, Y Hu, J Zhang - CAAI Transactions on Intelligence …, 2016 - Elsevier
In some complicated tabletop object manipulation task for robotic system, demonstration
based control is an efficient way to enhance the stability of execution. In this paper, we use a …

To imitate or not to imitate: Boosting reinforcement learning-based construction robotic control for long-horizon tasks using virtual demonstrations

L Huang, Z Zhu, Z Zou - Automation in Construction, 2023 - Elsevier
Construction robots controlled using reinforcement learning (RL) have recently emerged,
showing higher adaptability and self-learning intelligence over pre-programmed and …

Data mining approach for automatic ship-route design for coastal seas using AIS trajectory clustering analysis

D Zhang, Y Zhang, C Zhang - Ocean Engineering, 2021 - Elsevier
In this paper, we propose an automatic route design method based on simple recurrent unit
(SRU) and automatic identification system (AIS) data. Laplacian eigen maps and Gaussian …

Haptics electromyography perception and learning enhanced intelligence for teleoperated robot

C Yang, J Luo, C Liu, M Li… - IEEE Transactions on …, 2018 - ieeexplore.ieee.org
Due to the lack of transparent and friendly human-robot interaction (HRI) interface, as well
as various uncertainties, it is usually a challenge to remotely manipulate a robot to …

Transition state clustering: Unsupervised surgical trajectory segmentation for robot learning

S Krishnan, A Garg, S Patil, C Lea… - … journal of robotics …, 2017 - journals.sagepub.com
Demonstration trajectories collected from a supervisor in teleoperation are widely used for
robot learning, and temporally segmenting the trajectories into shorter, less-variable …

[HTML][HTML] Human–robot collaboration in sensorless assembly task learning enhanced by uncertainties adaptation via Bayesian Optimization

L Roveda, M Magni, M Cantoni, D Piga… - Robotics and Autonomous …, 2021 - Elsevier
Robots are increasingly exploited in production plants. Within the Industry 4.0 paradigm, the
robot complements the human's capabilities, learning new tasks and adapting itself to …