Xiaoliang Bai

Xiaoliang Bai

Visiting Researcher

Prof. Xiaoliang Bai is an Associate Professor at the School of Mechanical Engineering at the Northwestern Polytechnical University, China. His primary research interest is in Smart manufacturing and the use of advanced Human-Computer Interface technology to improve the intelligence of manufacturing systems. He is also interested in the Computer-aided design and studying technologies involved in CAD systems, e.g. reverse engineering, 3D model retrieval, gesture etc.

He completed his PhD in 2005 from the Northwestern Polytechnical University in Xian, China. He has been a visiting researcher at the HIT Lab New Zealand!

Publications

  • Haptic Feedback Helps Me? A VR-SAR Remote Collaborative System with Tangible Interaction
    Peng Wang, Xiaoliang Bai, Mark Billinghurst, Shusheng Zhang, Dechuan Han, Mengmeng Sun, Zhuo Wang, Hao Lv, Shu Han

    Wang, Peng, et al. "Haptic Feedback Helps Me? A VR-SAR Remote Collaborative System with Tangible Interaction." International Journal of Human–Computer Interaction (2020): 1-16.

    @article{wang2020haptic,
    title={Haptic Feedback Helps Me? A VR-SAR Remote Collaborative System with Tangible Interaction},
    author={Wang, Peng and Bai, Xiaoliang and Billinghurst, Mark and Zhang, Shusheng and Han, Dechuan and Sun, Mengmeng and Wang, Zhuo and Lv, Hao and Han, Shu},
    journal={International Journal of Human--Computer Interaction},
    pages={1--16},
    year={2020},
    publisher={Taylor \& Francis}
    }
    Research on Augmented Reality (AR)/Mixed Reality (MR) remote collaboration for physical tasks remains a compelling and dynamic area of study. AR systems have been developed which transmit virtual annotations between remote collaborators, but there has been little research on how haptic feedback can also be shared. In this paper, we present a Virtual Reality (VR)-Spatial Augmented Reality (SAR) remote collaborative system that provides haptic feedback with tangible interaction between a local worker and a remote expert helper. Using this system, we conducted a within-subject user study to compare two interfaces for remote collaboration between a local worker and expert helper, one with mid-air free drawing (MFD) and one with tangible physical drawing (TPD). The results showed that there were no significant differences with respect to performance time and operation errors. However, users felt that the TPD interface supporting passive haptic feedback could significantly improve the remote experts’ user experience in VR. Our research provides useful information on the way for gesture- and gaze-based multimodal interaction supporting haptic feedback in AR/MR remote collaboration on physical tasks.