Bob Percell, president of CAMotion, wants to put motion control within the reach of manufacturing processes that involve repetitive operations, but don't need expensive robotics. The company is using software algorithms developed at the Georgia Institute of Technology as the foundation of a motion-control system that will help manufacturers reduce labor involved with routine-inspection and material-handling tasks. Two types of algorithms are used in the CAMotion software. The first is a vibration-control algorithm that plans the robotic-axis trajectory. By damping out vibration, it allows use of lighter and less-expensive components. A learning algorithm helps the equipment improve its own performance. "Once the machine makes the moves through about five iterations, it learns the open loop, gets more accurate, and reduces the dynamic error by a factor of ten," says Purcell. The software also combines machine vision, encoders, and accelerometers for helping the system know its own location relative to the work. Percell says that software combined with smaller components can reduce automation costs from 10 to 30% in many applications.
The National Highway Traffic Safety Administrationís recent backup camera mandate could open the door to more vehicle innovations, including better graphical displays, 360-degree camera views, and the increased use of Ethernet.
With support from National Instruments, a group of dedicated students from Connally High School in Austin, where more than 50% of the students are at risk of not graduating, have created a successful robotics team that is competing in the FIRST World Championships.
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