A Distributed Architecture for Collaborative Teleoperation using Virtual Reality and Web Platforms

Domingues, Christophe; Otmane, Samir; Davesne, Frédéric; Mallem, Malik; Benchikh, Laredj

doi:10.1109/ccnc.2009.4784826

Cited by 8 publications

(4 citation statements)

References 9 publications

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“…Gathering the data necessary for system training can be thought of as an imitation learning task, where the trained HMM model parameters should be estimated such that the actions it produces to operate the robot arm imitate those of an experienced welder produces to teleoperate the same arm. While teleoperating the robot arm, sensors can be connected to the operators own arm (a virtual reality interface can be used to help the operator control the robot just as if he was at the welding site performing the welding task himself (Domingues et al, 2009)). Using a humanoid arm has the advantage that it allows the operator moves to be directly mapped to the robot arm joints positions.…”

Section: Discussionmentioning

confidence: 99%

A New Modular Strategy For Action Sequence Automation Using Neural Networks And Hidden Markov Models

Taher

Abdeljawad

2013

International Journal of System Dynamics Applications

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In this paper, the authors propose a new hybrid strategy (using artificial neural networks and hidden Markov models) for skill automation. The strategy is based on the concept of using an “adaptive desired” that is introduced in the paper. The authors explain how using an adaptive desired can help a system for which an explicit model is not available or is difficult to obtain to smartly cope with environmental disturbances without requiring explicit rules specification (as with fuzzy systems). At the same time, unlike the currently available hidden Markov-based systems, the system does not merely replay a memorized skill. Instead, it takes into account the current system state as reported by sensors. The authors approach can be considered a bridge between the spirit of conventional automatic control theory and fuzzy/hidden Markov-based thinking. To demonstrate the different aspects of the proposed strategy, the authors discuss its application to underwater welding automation.

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Section: Discussionmentioning

confidence: 99%

A New Modular Strategy For Action Sequence Automation Using Neural Networks And Hidden Markov Models

Taher

Abdeljawad

2013

International Journal of System Dynamics Applications

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“…Most of the research works studied consist of three control labs at most, and are located in the same university (Domingues et al, 2009;Moudgalya & Arora, 2010). On the contrary, the proposed Network of Control Remote Labs consists of several processes, many universities, and therefore, many users from different countries with different time zones, and it is expected to grow exponentially according to the number of universities and new processes linked to the System.…”

Section: Layer 2 Management and Administration Systemmentioning

confidence: 99%

“…We have mentioned some works that we consider relevant when deciding to adopt or discard some approaches. Domingues, Otmane, Davesne, Mallem, and Benchikh (2009) presented an extension of existing distributed software for collaborative teleoperation based on networked human-scaled mixed reality and mobile platforms, in which the first teleoperation system is composed by a Cþþ VR application with the use of OpenGL library, and the second system is composed by an applet-format JAVA Web Application. Tripicchio, Ruffaldi, Avizzano, and Bergamasco (2008) presented a distributed platform that provides researchers with a framework to develop and deploy multi-modal-enabled experiments and share them on the network with other research institutes.…”

Section: Other Approachesmentioning

confidence: 99%

A multi-user remote academic laboratory system

Barrios¹,

Panche²,

Duque³

et al. 2013

Computers & Education

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“…As shown in Fig. 10(c), the Augmented Reality Interface for Teleoperation (ARITI) project applies augmented reality to help human operators to achieve complex tasks, such as cooperative teleassistance (Domingues et al, 2009). Multiple operators control the virtual phantom robot to take virtual objects as a simulation.…”

Section: Virtual Collaboration For Communication Time Delaymentioning

confidence: 99%

Robotic remote control based on human motion via virtual collaboration system: A survey

Jung

Song

2018

JAMDSM

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This paper offers a review of the latest robotic remote control schemes that are based on human motion through the virtual collaboration system. The robotic remote control schemes have been studied and developed to combine the intelligence of humans with the precision and mechanical strength of robots. They have performed an important role in some dangerous environments by replacing humans in many difficult jobs, but the lack of intuitive control interfaces causes decreased efficiency. To address this problem, various approaches have been recently investigated, including human motion-based control, visual feedback systems, tactile or force feedback, and other various haptic systems. This paper describes the tendencies of these efforts and discusses possibilities and limitations in three parts: remote control based on human motion, multimodal feedback schemes for realistic interaction, and virtual collaboration systems.

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A Distributed Architecture for Collaborative Teleoperation using Virtual Reality and Web Platforms

Cited by 8 publications

References 9 publications

A New Modular Strategy For Action Sequence Automation Using Neural Networks And Hidden Markov Models

A New Modular Strategy For Action Sequence Automation Using Neural Networks And Hidden Markov Models

A multi-user remote academic laboratory system

Robotic remote control based on human motion via virtual collaboration system: A survey

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