Исследовательские работы
С использованием NOKOV Motion Capture

Liu H, Xie X, Li Y, et al. Leveraging Motion Capture System for High Accuracy AR-Assisted Assembly[C]//The International Conference on Computational Design and Robotic Fabrication. Singapore: Springer Nature Singapore, 2024: 77-90.

Zuo C, Huang J, Jiang X, et al. Transformer IMU calibrator: dynamic on-body IMU calibration for inertial motion capture[J]. ACM Transactions on Graphics (TOG), 2025, 44(4): 1-14.

Wang C, Cheng B, Tang Q, et al. Design and Validation of a Brain-Controlled Hip Exoskeleton for Assisted Gait Rehabilitation Training[J]. Micromachines, 2025, 16(12): 1364.

Wang H, Hou T, Liu T, et al. Encoded Marker Clusters for Auto-Labeling in Optical Motion Capture[J]. ACM Transactions on Graphics, 2025, 44(2): 1-16.

Dong Z C, Wu W, Xu Z, et al. Tailored reality: Perception-aware scene restructuring for adaptive vr navigation[J]. ACM Transactions on Graphics (TOG), 2021, 40(5): 1-15.

Wu Y, Chen S, Meng X, et al. Enabling 6d pose tracking on your acoustic devices[C]//Proceedings of the 22nd Annual International Conference on Mobile Systems, Applications and Services. 2024: 15-28.

Y. Li, J. Zhang, W. Xu, T. Tang and C. Lu, "FSGlove: An Inertial-Based Hand Tracking System with Shape-Aware Calibration," 2025 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), Hangzhou, China, 2025, pp. 18304-18311, doi: 10.1109/IROS60139.2025.11245803.

Nie B, Li Q, Gan S, et al. Safety envelope of pedestrians upon motor vehicle conflicts identified via active avoidance behaviour[J]. Scientific reports, 2021, 11(1): 3996.

Li Q, Shang S, Pei X, et al. Kinetic and kinematic features of pedestrian avoidance behavior in motor vehicle conflicts[J]. Frontiers in bioengineering and biotechnology, 2021, 9: 783003.

Li Q, Zhou Q, Chen W, et al. In Vivo Pedestrian Behaviour upon Motor Vehicle Conflicts: Experimental Framework and Initial Results[C]//Proceedings of IRCOBI Asia Conference. 2021: 1-2.

J. Fu et al., "Augmented Reality-Assisted Robot Learning Framework for Minimally Invasive Surgery Task," 2023 IEEE International Conference on Robotics and Automation (ICRA), London, United Kingdom, 2023, pp. 11647-11653