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.
Digital healthcare devices and wearable electronic products need to be thoroughly tested, lest they live short, ignominious lives, an expert will tell attendees at UBM’s upcoming Designers of Things conference in San Jose, Calif.
Designers of electronic interfaces will need to be prepared to incorporate haptics in next generation products, an expert will tell attendees at the upcoming Designers of Things conference in San Jose, Calif.
The company says it anticipates high-definition video for home security and other uses will be the next mature technology integrated into the IoT domain, hence the introduction of its MatrixCam devkit.
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