Research on human-robot interactions has been driven by the increasing employment of robotic manipulators in manufacturing and production. Toward developing more effective human-robot collaboration during shared tasks, this paper proposes an interaction scheme by employing machine learning algorithms to interpret biosignals acquired from the human user and accordingly planning the robot reaction. More specifically, a force myography (FMG) band was wrapped around the user\u27s forearm and was used to collect information about muscle contractions during a set of collaborative tasks between the user and an industrial robot. A recurrent neural network model was trained to estimate the user\u27s hand movement pattern based on the collected FMG d...
The context of this thesis is the collaboration between humans and machines in various industrial re...
The automation of human gestures is gaining increasing importance in manufacturing. Indeed, robots s...
One way of potentially improving the use of robots in a collaborative environment is through predict...
Research on human-robot interactions has been driven by the increasing employment of robotic manipul...
Human-robot collaboration in industrial settings calls for implementing safety measures to ensure th...
Physical human-robot interaction (pHRI) is reliant on human actions and can be addressed by studying...
By applying robots while collaborating with a human in an industrial setting to provide more flexibl...
Force myography (FMG) signals can read volumetric changes of muscle movements, while a human partici...
Consumer markets demonstrate an observable trend towards mass customization. Assembly processes are ...
In this study, human robot collaboration (HRC) via force myography (FMG) bio-signal was investigated...
Force myography (FMG) is a contemporary, non-invasive, wearable technology that can read the underly...
Human-robot collaboration is migrating from lightweight robots in laboratory environments to industr...
Inferring human operators' actions in shared collaborative tasks, plays a crucial role in enhancing ...
UK Research and Innovation, UKRI: EP/S033718/2, EP/T022493/1, EP/V00784XThis work is partially funde...
In industrial scenarios, requiring human–robot collaboration, the understanding between the human op...
The context of this thesis is the collaboration between humans and machines in various industrial re...
The automation of human gestures is gaining increasing importance in manufacturing. Indeed, robots s...
One way of potentially improving the use of robots in a collaborative environment is through predict...
Research on human-robot interactions has been driven by the increasing employment of robotic manipul...
Human-robot collaboration in industrial settings calls for implementing safety measures to ensure th...
Physical human-robot interaction (pHRI) is reliant on human actions and can be addressed by studying...
By applying robots while collaborating with a human in an industrial setting to provide more flexibl...
Force myography (FMG) signals can read volumetric changes of muscle movements, while a human partici...
Consumer markets demonstrate an observable trend towards mass customization. Assembly processes are ...
In this study, human robot collaboration (HRC) via force myography (FMG) bio-signal was investigated...
Force myography (FMG) is a contemporary, non-invasive, wearable technology that can read the underly...
Human-robot collaboration is migrating from lightweight robots in laboratory environments to industr...
Inferring human operators' actions in shared collaborative tasks, plays a crucial role in enhancing ...
UK Research and Innovation, UKRI: EP/S033718/2, EP/T022493/1, EP/V00784XThis work is partially funde...
In industrial scenarios, requiring human–robot collaboration, the understanding between the human op...
The context of this thesis is the collaboration between humans and machines in various industrial re...
The automation of human gestures is gaining increasing importance in manufacturing. Indeed, robots s...
One way of potentially improving the use of robots in a collaborative environment is through predict...