Horizon 2020 Marie Skłodowska-Curie Innovative Training Network

Siyuan Chen

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Siyuan Chen 2017-07-03T10:57:45+00:00
Early Stage Researcher
University College Dublin (Ireland)

Project 14: Reduction of uncertainty through regularized, automated road inspection

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Research Interests:

CAD/CAM; Additive manufacturing; Unmanned aerial vehicle application


Siyuan holds a MSc degree in Mechanical and Aerospace Engineering from Syracuse University. After receiving his Masters, he worked as a research assistant at Columbia University, in Numerical Modeling, and prior to, at Tsinghua University, developing and supporting interdisciplinary courses in Learning Process Design, and Workshop Management.

He received his bachelor degree from the Beijing Institute of Petrochemical Technology in Mechanical Engineering.

His previous research experience has included under-sea pipeline repair system design (as part of the China National Research Program), rescue equipment design and 3D printer design. He joined TRUSS ITN in September 2015.

Research Outputs:

  • Dou Y., Cai X.and Chen S. (2012), “Design of an Amphibious Rescuing Car Based on Fischertechnik Model”, Laboratory Research and Exploration, 31(6).
  • Chen S., Cai X. and Li H. (2012), P.R. China Patent ZL201120186204.0: Electromagnetically Locking Device for Automatic Window.
  • Han L., Liu Z. and Chen S. (2010), “Optimization of Automobile Suspension System Based on SUMT”, Science Technology and Engineering, 110(25).

Publications in TRUSS

This paper reports on patents worldwide related to both hardware and software for the contraction and deployment of UAVs and is intended to provide a snapshot of currently available unmanned aerial vehicles (UAVs) technologies, as well as to identify recent trends and future opportunities in affiliated hardware and software. Basic components related to self-designed units are explained (e.g. platform selection, autopilot control comparison and sensor selection). Current applications and research areas of UAVs are discussed. The research and product development trends focus on extending the flight time, enhancing the water and wind resistant capabilities, improving autonomous navigation abilities, and enriching the payload capacity. Since autonomous navigation is a key technology in UAVs applications, concepts about this are also explained. -> Link to full text in repository

DOI: http://dx.doi.org/10.2174/1872212110666160712230039

This paper introduces a three-dimensional reconstruction experiment based on a physical laboratory-based experiment on a brick wall. Using controlled shooting distances and angles, different images sets were captured and processed with a structure from motion based technique, which can reconstruct 3D models based on multi-view, Two-Dimensional (2D) images. Those 2D geometries are shown to generate significant deformations within the resulting point cloud, especially where there were large angles (with respect the camera position and the wall’s normal direction) and at close distances to the wall’s surface. This paper demonstrates that by overlapping different flawed image sets, the deformation problem can be minimised.