Results 21 to 30 of about 56,160 (238)

Admittance learning strategy using generalized simplex gradient methods for human–robot collaboration

Mechanical Engineering Journal, 2023
Human-Robot Collaboration (HRC) systems are becoming widespread in industrial applications owing to the advantages of enhancing work productivity and reducing production expenses.
Liem Duc TRAN, Tasuku YAMAWAKI, Hiroyuki FUJIWARA, Masahito YASHIMA   +3 more
doaj   +1 more source

Deep Deterministic Policy Gradient with Reward Function Based on Fuzzy Logic for Robotic Peg-in-Hole Assembly Tasks

Applied Sciences, 2022
Robot automatic assembly of weak stiffness parts is difficult due to potential deformation during assembly. The robot manipulation cannot adapt to the dynamic contact changes during the assembly process. A robot assembly skill learning system is designed
Ziyue Wang, Fengming Li, Yu Men, Tianyu Fu, Xuting Yang, Rui Song   +5 more
doaj   +1 more source

A Framework for Composite Layup Skill Learning and Generalizing Through Teleoperation

Frontiers in Neurorobotics, 2022
In this article, an impedance control-based framework for human-robot composite layup skill transfer was developed, and the human-in-the-loop mechanism was investigated to achieve human-robot skill transfer.
Weiyong Si, Ning Wang, Qinchuan Li, Chenguang Yang   +3 more
doaj   +1 more source

Learning Variable Impedance Control for Contact-rich Robotics Manipulation with Guaranteed Passivity

IFAC-PapersOnLine
Xiao Yang, Che Hou, Yanhao He, Xiaoyu Zhang, Wenjie Chen, Zheng Chen   +5 more
openaire   +2 more sources

Deep Learning-Based Recognition of Unsafe Acts in Manufacturing Industry

IEEE Access, 2023
Despite technological progress and the tendency for automation, the majority of manufacturing workplaces still rely on human labor. Although industrial tasks are frequently composed of simple operator actions, non-ergonomic execution of such repetitive ...
Arso M. Vukicevic, Milos N. Petrovic, Nikola M. Knezevic, Kosta M. Jovanovic   +3 more
doaj   +1 more source

Fault Detection and Classification in Transmission Lines Connected to Inverter-Based Generators Using Machine Learning

Energies, 2022
Integrating inverter-based generators in power systems introduces several challenges to conventional protection relays. The fault characteristics of these generators depend on the inverters’ control strategy, which matters in the detection and ...
Khalfan Al Kharusi, Abdelsalam El Haffar, Mostefa Mesbah   +2 more
doaj   +1 more source

Exploiting sensorimotor stochasticity for learning control of variable impedance actuators [PDF]

2010 10th IEEE-RAS International Conference on Humanoid Robots, 2010
Novel anthropomorphic robotic systems increasingly employ variable impedance actuation in order to achieve robustness to uncertainty, superior agility and efficiency that are hallmarks of biological systems. Controlling and modulating impedance profiles such that it is optimally tuned to the controlled plant is crucial to realise these benefits.
Mitrovic, Djordje, Klanke, Stefan, Howard, Matthew, Vijayakumar, Sethu   +3 more
openaire   +2 more sources

Efficient learning variable impedance control for industrial robots

Bulletin of the Polish Academy of Sciences: Technical Sciences, 2023
. Compared with the robots, humans can learn to perform various contact tasks in unstructured environments by modulating arm impedance characteristics. In this article, we consider endowing this compliant ability to the industrial robots to effectively ...
Chao Li, Z. Zhang, Guihua Xia, Xie Xin-ru, Qidan Zhu   +4 more
semanticscholar   +1 more source

Variable Impedance Control - A Reinforcement Learning Approach

Robotics: Science and Systems VI, 2010
One of the hallmarks of the performance, versatility, and robustness of biological motor control is the ability to adapt the impedance of the overall biomechanical system to different task requirements and stochastic disturbances. A transfer of this principle to robotics is desirable, for instance to enable robots to work robustly and safely in ...
Jonas Buchli, Evangelos Theodorou, Freek Stulp, Stefan Schaal   +3 more
openaire   +1 more source

Learning Variable Impedance Control for Aerial Sliding on Uneven Heterogeneous Surfaces by Proprioceptive and Tactile Sensing [PDF]

IEEE Robotics and Automation Letters, 2022
The recent development of novel aerial vehicles capable of physically interacting with the environment leads to new applications such as contact-based inspection. These tasks require the robotic system to exchange forces with partially-known environments,
Weixuan Zhang, Lionel Ott, M. Tognon, R. Siegwart   +3 more
semanticscholar   +1 more source