"If you look at what people do in factories, direct labor is now almost entirely used for motion," says Steve Dickerson, chairman of CAMotion and a professor emeritus at Georgia Tech. "The fact that people have good hand-eye coordination and the intelligence to know the next task means that people in manufacturing are used almost exclusively for moving things around. These tasks do not require the same precision as placing components on a circuit board, but [they do require] large-scale motions across three dimensions [that are] difficult to automate in a cost-effective way."

CAMotion's first customer is painting company Vulcan Group (Birmingham, AL). The company uses two CAMotion systems: one to inspect automobile roof racks after painting and the other to stack the completed parts in a shipping container. As part of the inspection task, a gantry-type robot moves both the parts and the vision system to acquire 24 different images of each part.

Georgia Tech researchers developed three types of algorithms included in CAMotion's software:

• A vibration control algorithm plans the robotic axis trajectory in such a way as to avoid creat-ing unnecessary oscillation.By "damping out" the vibration, the "intelligent trajectory" allows the use of lighter and less expensive components.
• A learning algorithm helps the equipment improve its own performance based on feedback. This typically produces a 10-to-1 reduction in dynamic error.
• Position estimation software, combining machine vision, encoders and accelerometers, helps the system know its own location relative to the work and thus how to move to accomplish a task.

For more information, call CAMotion at 404-874-0090.