A shared control architecture based on electrooculogram signal and global vision for smart assistive robots

2017 ◽  
Author(s):  
Lei Sun ◽  
Hua Chen ◽  
YangQuan Chen
Keyword(s):  
Shared Control ◽  
Control Architecture ◽  
Assistive Robots ◽  
Global Vision

scholarly journals A Haptic Shared-Control Architecture for Guided Multi-Target Robotic Grasping

2020 ◽  
Vol 13 (2) ◽  
pp. 270-285 ◽  
Author(s):  
Firas Abi-Farraj ◽  
Claudio Pacchierotti ◽  
Oleg Arenz ◽  
Gerhard Neumann ◽  
Paolo Robuffo Giordano
Keyword(s):  
Shared Control ◽  
Control Architecture ◽  
Robotic Grasping

DESIGNING INTELLIGENT SOCIALLY ASSISTIVE ROBOTS AS EFFECTIVE TOOLS IN COGNITIVE INTERVENTIONS

2011 ◽  
Vol 08 (01) ◽  
pp. 103-126 ◽  
Author(s):  
JEANIE CHAN ◽  
GOLDIE NEJAT ◽  
JINGCONG CHEN
Keyword(s):  
Cognitive Stimulation ◽  
Human Robot Interaction ◽  
Control Architecture ◽  
Cognitive Interventions ◽  
Training Interventions ◽  
Assistive Robots ◽  
Socially Assistive Robots ◽  
Assistive Robot ◽  
Term Basis ◽  
Socially Assistive Robot

Recently, there has been a growing body of research that supports the effectiveness of using non-pharmacological cognitive and social training interventions to reduce the decline of or improve brain functioning in individuals suffering from cognitive impairments. However, implementing and sustaining such interventions on a long-term basis is difficult as they require considerable resources and people, and can be very time-consuming for healthcare staff. Our research focuses on making these interventions more accessible to healthcare professionals through the aid of robotic assistants. The objective of our work is to develop an intelligent socially assistive robot with abilities to recognize and identify human affective intent to determine its own appropriate emotion-based behavior while engaging in assistive interactions with people. In this paper, we present the design of a novel human-robot interaction (HRI) control architecture that allows the robot to provide social and cognitive stimulation in person-centered cognitive interventions. Namely, the novel control architecture is designed to allow a robot to act as a social motivator by encouraging, congratulating and assisting a person during the course of a cognitively stimulating activity. Preliminary experiments validate the effectiveness of the control architecture in providing assistive interactions during a HRI-based person-directed activity.

Social Intelligence for a Task-Driven Assistive Robot

2010 ◽  
Author(s):  
Goldie Nejat ◽  
Maurizio Ficocelli
Keyword(s):  
Social Intelligence ◽  
Effective Interaction ◽  
Well Being ◽  
Emotional Behavior ◽  
Control Architecture ◽  
Patient Centered ◽  
Assistive Robots ◽  
Assistive Robot ◽  
Emotional Model ◽  
Socially Assistive Robot

The objective of a socially assistive robot is to create a close and effective interaction with a human user for the purpose of giving assistance. In particular, the social interaction, guidance and support that a socially assistive robot can provide a person can be very beneficial to patient-centered care. However, there are a number of conundrums that must be addressed in designing such a robot. This work addresses one of the main limitations in the development of intelligent task-driven socially assistive robots: Robotic control architecture design and implementation with explicit social and assistive task functionalities. In particular, in this paper, a unique emotional behavior module is presented and implemented in a learning-based control architecture for human-robot interactions (HRI). The module is utilized to determine the appropriate emotions of the robot, as motivated by the well-being of the person, during assistive task-driven interactions. A novel online updating technique is used in order to allow the emotional model to adapt to new people and scenarios. Preliminary experiments presented show the effectiveness of utilizing robotic emotional assistive behavior during HRI in assistive scenarios.

Four-Channel Control Architectures for Bilateral and Multilateral Teleoperation

2013 ◽  
pp. 283-298
Author(s):  
Yuji Wang ◽  
Fuchun Sun ◽  
Huaping Liu
Keyword(s):  
Time Delay ◽  
Large Time ◽  
Force Feedback ◽  
The Other ◽  
Shared Control ◽  
Control Architecture ◽  
Channel Control ◽  
Channel Architecture

The four-channel architecture in teleoperation with force feedback has been studied in various existing literature. However, most of them focused on Lawrence architecture and did not research other cases. This paper proposes two other four-channel architectures: passive four-channel architecture and passive four-channel architecture with operator force. Furthermore, two types of multilateral shared control architecture based on passive four-channel architecture, which exists in space teleoperation, are put forward. One is dual-master multilateral shared control architecture, and the other is dual-slave multilateral shared control architecture. Simulations show that these four architectures can maintain stability in the presence of large time delay.

Shared control architectures for haptic training: Performance and coupled stability analysis

2011 ◽  
Vol 30 (13) ◽  
pp. 1627-1642 ◽  
Author(s):  
Behzad Khademian ◽  
Keyvan Hashtrudi-Zaad
Keyword(s):  
Network Model ◽  
User Study ◽  
Operating Conditions ◽  
Shared Control ◽  
Control Architecture ◽  
Training Performance ◽  
Training Simulation ◽  
Haptic Simulation ◽  
Simulation Systems ◽  
Dual User

A novel shared control architecture is presented for dual-user haptic training simulation systems for enhanced interaction between the users and between each user and the virtual environment. The coupled stability of the proposed control architecture against uncertainties in the environment and the user’s dynamics is investigated using the three-port master–slave network model of the dual-user haptic simulation system. For this purpose, Llewellyn’s unconditional stability criterion is applied to an equivalent two-port network model obtained from the corresponding three-port network, considering the environment as a load termination. The kinesthetic performance of the proposed architecture is numerically analyzed for transparency and evaluated against a benchmark control architecture under different operating conditions, such as various types of environments, users’ grasps, and levels of dominance of users over the task. An experimental user study is carried out to assess the effectiveness of the proposed architecture in terms of users’ perception of environment stiffness sensing, device agility, and haptic guidance reception.

scholarly journals A learning-based shared control architecture for interactive task execution

2017 ◽  
Author(s):  
Firas Abi-Farraj ◽  
Takayuki Osa ◽  
Nicolo Pedemonte Jan Peters ◽  
Gerhard Neumann ◽  
Paolo Robuffo Giordano
Keyword(s):  
Shared Control ◽  
Control Architecture ◽  
Task Execution ◽  
Interactive Task
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