Post Bachelor
The Intelligent Systems Division at NIST is investigating the performance of 3D machine vision systems for various manufacturing applications. The research will focus on conducting experiments and analyzing data in relation to understanding the performance of 3D machine vision systems to support the development of standards for measuring the depth error and depth resolution of these systems, as well as for measuring the performance of systems used for bin picking applications.
Research whether the distribution of the depth error across a single image at a certain distance is “the same” as the distribution of the depth error across a single image taken from a significantly different distance. Research the effects of various factors (part color, part surface properties, bin color, bin depth, ratio of part size to bin size, part distribution in a bin) on bin picking performance (e.g., cycle time, pose uncertainty, etc.).
Not all the qualifications below are required.
● Education: Engineering majors with bachelor’s/master’s degree, or in final or penultimate
years of bachelor’s/master’s degree.
● Programming experience in one or more of the following computer languages: C++,
Python, Java
● Experience with CAD software such as SolidWorks
● Experience using MATLAB.
● Experience using 3D printers.
● Basic understanding of robot control theory (DH parameters, kinematics, etc.)
● Basic understanding of 3D sensors such as LiDAR or RGBD cameras
● Basic understanding of the Unix/Linux operating systems
● Basic understanding of programming robot forward and inverse kinematics
● Working knowledge of 3D point cloud data processing techniques using Point Cloud
● Library (PCL - http://pointclouds.org), CloudCompare, or other similar tools
Collect data from various 3D imaging systems.
● Program collaborative robot arms for conducting various tasks.
● Use metrology systems (e.g., laser trackers, CMMs, etc.) for establishing reference
measurements.
● Use analysis software (e.g., MATLAB, Spatial Analyzer, Polyworks, Excel, etc.) to
interpret results and produce visualizations.
● Write reports and contribute to peer-reviewed publications.