2D machine vision established a field of engineering that maintains a direct and significant impact on the automation of many areas of manufacturing and logistics. 3D machine vison development aims to have the same impact on modern automation. The improved precision and accuracy that accompanies 3D vision, a result of the explicit method of capture, allows for the development of more complex operations. Object recognition and pose estimation of complex bodies allows for the integration of automated robotic manipulators in assembly lines, 3D field analysis allows for fast and accurate safety field evaluation aiding in the interaction and movement of objects in 3D space. Development in this field began 20 years ago, however the field of research is still in it’s early stages.  The focus of current work at the School of Mechanical & Aerospace Engineering is on object data simulation and the development of a software framework that will aid in future research and development for driverless vehicles in logistics. This is particularly important in unstructured environments where the vehicles themselves need to process images in real time in order to manage loads which vary from pallet to pallet. Examples of this research can be found here and here.