Effects of Augmented Reality on the Performance of Teleoperated Industrial Assembly Tasks in a Robotic Embodiment

Brizzi, Filippo; Peppoloni, Lorenzo; Graziano, Alessandro Di; Stefano, Erika Di; Avizzano, Carlo Alberto; Ruffaldi, Emanuele

doi:10.1109/thms.2017.2782490

Cited by 65 publications

(47 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, different types of cameras are utilized in AR research, such as RGB-D, binocular, stereo, depth, infrared, monocular, pinhole, wide-angle and omnidirectional cameras. In custom setups, VR headsets (Oculus Rift and Oculus DK2) were also adapted as AR displays [38][39][40][41].…”

Section: Ar Technologymentioning

confidence: 99%

“…ROS (Robot Operating System) was employed as the main platform for data sharing and system integration. Another example of robot teleoperation with AR-based visual feedback was invented by Brizzi et al [39]. The authors discussed how AR can improve the sense of embodiment in HRI based on experiments with Baxter robot which was teleoperated in an industrial assembly scenario.…”

Section: Ar For Human-robot Interactionmentioning

confidence: 99%

See 1 more Smart Citation

Augmented Reality for Robotics: A Review

2020

View full text Add to dashboard Cite

Augmented reality (AR) is used to enhance the perception of the real world by integrating virtual objects to an image sequence acquired from various camera technologies. Numerous AR applications in robotics have been developed in recent years. The aim of this paper is to provide an overview of AR research in robotics during the five year period from 2015 to 2019. We classified these works in terms of application areas into four categories: (1) Medical robotics: Robot-Assisted surgery (RAS), prosthetics, rehabilitation, and training systems; (2) Motion planning and control: trajectory generation, robot programming, simulation, and manipulation; (3) Human-robot interaction (HRI): teleoperation, collaborative interfaces, wearable robots, haptic interfaces, brain-computer interfaces (BCIs), and gaming; (4) Multi-agent systems: use of visual feedback to remotely control drones, robot swarms, and robots with shared workspace. Recent developments in AR technology are discussed followed by the challenges met in AR due to issues of camera localization, environment mapping, and registration. We explore AR applications in terms of how AR was integrated and which improvements it introduced to corresponding fields of robotics. In addition, we summarize the major limitations of the presented applications in each category. Finally, we conclude our review with future directions of AR research in robotics. The survey covers over 100 research works published over the last five years.

show abstract

Section: Ar Technologymentioning

confidence: 99%

Section: Ar For Human-robot Interactionmentioning

confidence: 99%

Augmented Reality for Robotics: A Review

2020

View full text Add to dashboard Cite

show abstract

“…Manipulation of the observed space via AR was analyzed in robot teleoperation studies by Brizzi and Peppoloni et al in [69,70]. A headset-based AR environment was used to give a first-person perspective of the robot arm actuation, with AR cues added for robot arm's motion vectors.…”

Section: Improving Perception or Task Performance With Armentioning

confidence: 99%

“…the operated machinery is seen from outside, since first-person views i.e. views of the operated machinery from inside or ego-centric perspective have been covered in remote control teleoperation by [69,70]. The AR factor was varied by three Augmentation designs-a target-specific marker (A1), a 2D grid-map (A2) and a 3D scaling cube Fig.…”

Section: Experiments Designmentioning

confidence: 99%

“…In each test run, the participants were asked to navigate and accurately touch highlighted targets in the test area, using the remote control excavator's arm. This is a combination of the locomotion and pick-and-place tasks commonly used for depth estimation and positioning assessment [53,[69][70][71]76], adapted to the context of remotely controlling industrial machinery. The targets were highlighted in random order, and participants were scored on the number of targets reached.…”

Section: Experiments Designmentioning

confidence: 99%

See 1 more Smart Citation

Joint effects of depth-aiding augmentations and viewing positions on the quality of experience in augmented telepresence

et al. 2020

View full text Add to dashboard Cite

Virtual and augmented reality is increasingly prevalent in industrial applications, such as remote control of industrial machinery, due to recent advances in head-mounted display technologies and low-latency communications via 5G. However, the influence of augmentations and camera placement-based viewing positions on operator performance in telepresence systems remains unknown. In this paper, we investigate the joint effects of depth-aiding augmentations and viewing positions on the quality of experience for operators in augmented telepresence systems. A study was conducted with 27 non-expert participants using a real-time augmented telepresence system to perform a remote-controlled navigation and positioning task, with varied depth-aiding augmentations and viewing positions. The resulting quality of experience was analyzed via Likert opinion scales, task performance measurements, and simulator sickness evaluation. Results suggest that reducing the reliance on stereoscopic depth perception via camera placement has a significant benefit to operator performance and quality of experience. Conversely, the depth-aiding augmentations can partly mitigate the negative effects of inferior viewing positions. However the viewing-position based monoscopic and stereoscopic depth cues tend to dominate over cues based on augmentations. There is also a discrepancy between the participants' subjective opinions on augmentation helpfulness, and its observed effects on positioning task performance.

show abstract