Canadian Manufacturing

Auto manufacturing through robotic eyes

February 10, 2010  by Noelle Stapinsky, Features Editor

With just two tiny cameras connected to a circuit board and a three-minute technology pitch, Siddhant Ahuja was handed a $10,000 scholarship.

The PhD student from the University of Windsor presented his work on smart cameras used for quality control, assembly and robotic guidance to a panel of Dragon’s Den-like judges at the 2010 AUTO21 TestDRIVE competition in Ottawa and took top prize.

Working under Dr. Jonathan Wu, a professor and Canada Research Chair in automotive sensors and sensing systems, Ahuja said he started with a problem description: auto manufacturers need to constantly reconfigure their facilities to produce new car models.

Conventional wireless communication monitoring systems are unreliable on auto assembly lines due to radio frequency interference from the harsh conditions.


Currently auto manufacturers use cameras on assembly lines, but a single camera is unable to perceive distances between objects. These cameras are often connected to computers, then to network equipment and then to servers.

“A significant part of manufacturing relies on industrial robots, which are preprogrammed by a human operator. If one of the robots goes out of sync or malfunctions, the whole production line shuts down,” says Ahuja. “My idea is to provide these robots with their own set of eyes and connect them to an intelligent network that will enable them to communicate to each other and cooperatively achieve whatever the end goal is.”

“If a central node shuts down, everything shuts down. There’s a lot of infrastructure and maintenance costs associated with this,” says Ahuja.

All of these single vision cameras are sending gigabytes and of information to a central computer for processing.

To stream line this process and increase efficiency on the plant floor, Ahuja built a tiny module with two cameras to give industrial robots a 3D optical view of production. This “sight” enables the robots to detect shapes, colour and distances between objects.