A video demonstrating the autonomous Landing system developed for UAV in the following papers.
  1. G. Niu, L. Wu, Y. Gao and M.O. Pun, Unmanned Aerial Vehicle (UAV)-Assisted Path Planning for Unmanned Ground Vehicles (UGVs) via Disciplined Convex-Concave Programming, accepted for publication in the IEEE Trans. on Vehicular Technology, April 2022.
  2. G. Niu, Q. Yang, Y. Gao, M.O. Pun, Vision-based Autonomous Landing for Unmanned Aerial and Mobile Ground Vehicles Cooperative Systems, the IEEE Robotics and Automation Letters (RA-L), Vol.7, pp. 6234-6241, Jul. 2022.
  3. G. Niu, J. Li, S. Guo, M.O. Pun, L. Hou and L. Yang, "SuperDock: A Deep Learning-Based Automated Floating Trash Monitoring System", Proc. 2019 IEEE International Conference on Robotics and Biomimetics (Robio), Dali, China, December 6-8, 2019.

A video demonstrating the indoor positioning techniques developed in the following papers.
  1. S. Guo, G. Niu, Z. Wang, M.O. Pun and K. Yang, An Indoor Knowledge Graph Framework for Efficient Pedestrian Localization, the IEEE Sensors Journal, Vol. 21, No. 4, pp. 5151-5163, Feb. 2021.
  2. S. Guo and M.O. Pun, Indoor Semantic-Rich Link-Node Model Construction Using Crowdsourced Trajectories from Smartphones, the IEEE Sensors Journal, Vol. 19, No. 22, pp. 10917-10934, November 2019.

A video demonstrating the UAV-assisted Unmmaned Ground Vehicles reported in the following paper.
  1. Y. Wei, H. Qiu, Y. Liu, J. Du and M. Pun, "Unmanned aerial vehicle (UAV)-assisted unmanned ground vehicle (UGV) systems design, implementation and optimization," 2017 3rd IEEE International Conference on Computer and Communications (ICCC), Chengdu, 2017, pp. 2797-2801.