Automated AI Photogrammetry Robot


UBC Studios’ current photogrammetry system can create 3D models; however, it is limited to small objects that can be placed on a turntable. The motorized turntable also cannot properly scan objects with multiple convex or concave surfaces, due to the cameras being in a fixed position relative to the turntable. UBC Studios seeks to have a system in place to create 3D models that are completely automated, mobile, and is capable of taking pictures of objects on the scale of furniture.


The objective of this ECE Capstone project was to design and simulate a mobile photogrammetry robot that will enable the precise capture of the object using algorithms and sensory data.


The team was able to build a robotic solution for moving the cameras, positioning the rig, and adjusting a few
physical features of the camera itself like zooming and adjusting focus. Utilizing its free ranging wheels and vertical chain drive, the robot can scan large objects such as furniture. Additionally, the system is automated to reduce workload and time spent creating the 3D scans. The robot autonomously determines photo locations, uses VR tracking to orient the camera, and takes a photo of the object at each location. With this, the series of standard photos are combined into a 3D model.


The next steps for this project would be to build a physical model and work on integration and testing of sections of the robot that were only tested through simulation. More work could also be done for the body, in particular working on the placement of all the components within the frame and expanding the wheel control system and communication protocols. The image capture process can also be improved by adding more user inputs. Doing so would make the image capture process more customizable depending on the object being scanned.

The Team

UBC Studios Advisor

    Michal Suchanek

ECE Capstone Team

  • Estalin Alvarez
  • Robert Bradley
  • Sam Bedry
  • Seth Whalen
  • Tarryn MacPherson