Clustering of Emotional States under Different Task Difficulty Levels for the Robot-assisted Rehabilitation system-RehabRoby

Author(s):  
Yigit Can Aypar ◽  
Yunus Palaska ◽  
Ramazan Gokay ◽  
Engin Masazade ◽  
Duygun Erol Barkana ◽  
...  
Author(s):  
Serge Thill ◽  
Cristina A Pop ◽  
Tony Belpaeme ◽  
Tom Ziemke ◽  
Bram Vanderborght

AbstractRobot-assisted therapy (RAT) is an emerging field that has already seen some success and is likely to develop in the future. One particular application area is within therapies for autism spectrum disorders, in which the viability of the approach has been demonstrated.The present paper is a vision paper with the aim of identifying research directions in the near future of RAT. Specifically, we argue that the next step in such therapeutic scenarios is the development of more substantial levels of autonomy which would allow the robot to adapt to the individual needs of children over longer periods of time (while remaining under the ultimate supervision of a therapist). We argue that this requires new advances on the level of robot controllers as well as the ability to infer and classify intentions, goals and emotional states of the robot’s interactants. We show that the state of the art in a number of relevant disciplines is now at the point at which such an endeavour can be approached in earnest.


Author(s):  
Siniša Slavnić ◽  
Adrian Leu ◽  
Danijela Ristić-Durrant ◽  
Axel Gräser

For the purpose of developing robot-assisted human walking systems, human and robot walking dynamics are modeled using models of different complexity depending on simulation scenarios in different phases of robotic system development and selected walking parameters to be analyzed. This paper addresses the early modeling and simulation phase of the development of a novel mobile robot-assisted gait rehabilitation system to be used as a demonstrator for a cognitive robot control architecture currently under development. For simulation purposes dynamical models of walking human and powered orthosis are developed in multi-body simulation software (MSC Adams) using the LifeMod plug-in while the control algorithms are developed in Matlab. The paper introduces a novel ROS (Robot Operating System) based communication established between the real system software modules and the simulation environment. The performance evaluation was performed by running the simulation with motion data which were obtained using marker-based motion capture system and which were implemented as ROS node.


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