Dr Fangyi Zhang
Faculty of Engineering,
School of Electrical Engineering & Robotics
Personal details
Positions
- Research Fellow in Manipulation and Vision
Faculty of Engineering,
School of Electrical Engineering & Robotics
Qualifications
- PhD (Queensland University of Technology)
Publications
- Zhang, F., Leitner, J., Ge, Z., Milford, M. & Corke, P. (2019). Adversarial discriminative sim-to-real transfer of visuo-motor policies. International Journal of Robotics Research, 38(10-11), 1229–1245.
- Zhang, F., Leitner, J., Milford, M. & Corke, P. (2017). Modular deep Q networks for sim-to-real transfer of visuo-motor policies. Proceedings of the Australasian Conference on Robotics and Automation 2017, 1–10. https://eprints.qut.edu.au/115232
- Dean, J., Durham, J., Cooper, M., Eich, M., Lehnert, C., Mangels, R., McCool, C., Kujala, P., Nicholson, L., Pham, T., Sergeant, J., Wu, L., Zhang, F., Upcroft, B., Corke, P., Leitner, J., Tow, A. & Suenderhauf, N. (2017). The ACRV picking benchmark: A robotic shelf picking benchmark to foster reproducible research. Proceedings of the 2017 IEEE International Conference on Robotics and Automation (ICRA), 4705–4712. https://eprints.qut.edu.au/107170
- Zhang, F., Leitner, J., Milford, M. & Corke, P. (2017). Tuning modular networks with weighted losses for hand-eye coordination. Proceedings - 30th IEEE Conference on Computer Vision and Pattern Recognition Workshops, CVPRW 2017, 496–497. https://eprints.qut.edu.au/106963
- Qiu, K., Zhang, F. & Liu, M. (2016). Let the light guide us: VLC-based localization. IEEE Robotics and Automation Magazine, 23(4), 174–183.
- Zhang, F., Leitner, J., Milford, M., Upcroft, B. & Corke, P. (2015). Towards vision-based deep reinforcement learning for robotic motion control. Proceedings of the Australasian Conference on Robotics and Automation 2015, 1–8. https://eprints.qut.edu.au/92332
- Qiu, K., Zhang, F. & Liu, M. (2015). Visible Light Communication-based indoor localization using Gaussian Process. Proceedings of the 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2015), 3125–3130. https://eprints.qut.edu.au/101048
QUT ePrints
For more publications by Fangyi, explore their research in QUT ePrints (our digital repository).
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