Email: dbarnes_at_robots.ox.ac.uk

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Dan joined the Oxford Robotics Institute as a DPhil student in 2015 after completing his undergraduate studies in Engineering Science at Keble College. Dan’s Masters research project was also with ORI working on online traffic light detection.

His research currently focuses on robot perception and planning for autonomous vehicles. Current areas of interest include path planning in complex urban environments, object detection in continuous 3D data and GPU based dense disparity estimation.

 


Publications

2017

  • [PDF] B. Yeomans, H. Porav, M. Gadd, D. Barnes, J. Dequaire, T. Wilcox, S. Kyberd, S. Venn, and P. Newman, “MURFI 2016 – From Cars to Mars: Applying Autonomous Vehicle Navigation Methods To a Space Rover Mission,” in Proceedings of the 14th Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA), Leiden, Netherlands, 2017.
    [Bibtex]

    @inproceedings{BrianYeomansASTRA2017,
    author = {Yeomans, Brian and Porav, Horia and Gadd, Matthew and Barnes, Dan and Dequaire, Julie and Wilcox, Tom and Kyberd, Stephen and Venn, Simon and Newman, Paul},
    title = {MURFI 2016 - From Cars to Mars: Applying Autonomous Vehicle Navigation Methods To a Space Rover Mission},
    booktitle = {Proceedings of the 14th Symposium on Advanced Space Technologies in Robotics and Automation (ASTRA)},
    address = {Leiden, Netherlands},
    year = {2017},
    pdf = {http://www.robots.ox.ac.uk/~mobile/Papers/2017ASTRA_yeomans.pdf}
    }

  • [PDF] D. Barnes, W. Maddern, and I. Posner, “Find Your Own Way: Weakly-Supervised Segmentation of Path Proposals for Urban Autonomy,” in Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Singapore, 2017.
    [Bibtex]

    @inproceedings{BarnesICRA2017,
    Address = {Singapore},
    Author = {Barnes, Dan and Maddern, Will and Posner, Ingmar},
    Booktitle = {Proceedings of the IEEE International Conference on Robotics and Automation (ICRA)},
    Month = {June},
    Pdf = {https://arxiv.org/pdf/1610.01238v2},
    URL = {https://arxiv.org/abs/1610.01238},
    Title = "{Find Your Own Way: Weakly-Supervised Segmentation of Path Proposals for Urban Autonomy}",
    Year = {2017}}

2015

  • [PDF] D. Barnes, W. Maddern, and I. Posner, “Exploiting 3D Semantic Scene Priors for Online Traffic Light Interpretation,” in Proceedings of the IEEE Intelligent Vehicles Symposium (IV), Seoul, South Korea, 2015.
    [Bibtex]

    @inproceedings{BarnesIV2015,
    Address = {Seoul, South Korea},
    Author = {Barnes, Dan and Maddern, Will and Posner, Ingmar},
    Booktitle = {{P}roceedings of the {IEEE} {I}ntelligent {V}ehicles {S}ymposium ({IV})},
    Month = {June},
    Pdf = {http://www.robots.ox.ac.uk/~mobile/Papers/2015IV_barnes.pdf},
    Title = {{E}xploiting {3D} {S}emantic {S}cene {P}riors for {O}nline {T}raffic {L}ight {I}nterpretation},
    Year = {2015}}