Demo: Wireless VR/Haptic Open Platform for Multimodal Teleoperation

Jung, Tae Hun; Yoo, Han-Ju; Jin, Yuna; Rhee, Chae Eun; Chae, Chan-Byoung

doi:10.1109/wcncw48565.2020.9124746

Cited by 4 publications

(1 citation statement)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the haptic robot case [15], the testbed contains a Robotto-XR link from the panoramic camera to the controller with one 360°VR video stream, and bidirectional XR-Robot links between two Geomagic Touch robot arms with force-feedback. For the Robot-to-XR link, the 360°video feed comes from a Ricoh Theta to a Vive Cosmos VR headset, supported by an Nvidia Jetson TX2 edge server for video compression.…”

Section: Case Study and Testbedmentioning

confidence: 99%

A Vision of XR-aided Teleoperation System Towards 5G/B5G

Hu,

Deng,

Zhou

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Extended Reality (XR)-aided teleoperation has shown its potential in improving operating efficiency in missioncritical, rich-information and complex scenarios. The multisensory XR devices introduce several new types of traffic with unique quality-of-service (QoS) requirements, which are usually defined by three measures-human perception, corresponding sensors, and present devices. To fulfil these requirements, cellularsupported wireless connectivity can be a promising solution that can largely benefit the Robot-to-XR and the XR-to-Robot links. In this article, we present industrial and piloting use cases and identify the service bottleneck of each case. We then cover the QoS of Robot-XR and XR-Robot links by summarizing the sensors' parameters and processing procedures. To realise these use cases, we introduce potential solutions for each case with cellular connections. Finally, we build testbeds to investigate the effectiveness of supporting our proposed links using current wireless topologies.

show abstract

Section: Case Study and Testbedmentioning

confidence: 99%

A Vision of XR-aided Teleoperation System Towards 5G/B5G

Hu,

Deng,

Zhou

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

show abstract

Latency mitigation using applied HMMs for mixed reality-enhanced intuitive teleoperation in intelligent robotic welding

Lloyd

Chen

et al. 2023

Int J Adv Manuf Technol

View full text Add to dashboard Cite

Latency mitigation is crucial to increasing operational success, ease of use, and product quality in telemanipulation tasks when remotely guiding complex robotic systems. Hardware limitations have created a gap in performance optimization due to large teleoperation delays, which machine learning techniques could fill with lower time, improved performance, and reduced operating costs. Hidden Markov models (HMMs), in particular, have been explored to alleviate the issue due to their relative ease of use. A mixed reality-enhanced intuitive teleoperation framework for immersive and intuitive telerobotic welding is presented. The proposed system implements an HMM generative algorithm to learn and predict human-welder motion to enable a low-cost solution, combining smoothing and forecasting techniques to minimize robotic teleoperation time delay. The predicted welding motion system is simple to implement, can be used as a general solution to solve time delays, and is accurate. More specifically, it provides a 66% RMSE reduction compared to the application without HMM, which may be further optimized by up to 38%. Experiments show the HMM generative algorithm lets humans conduct tele-robot-assisted welding with better performance.

show abstract