Improving Robotic Accuracy through Iterative Teaching
Industrial robots have been around since the 1960s and their introduction into the manufacturing industry has helped in automating otherwise repetitive and unsafe tasks, while also increasing the performance and productivity for the companies that adopted the technology. As the majority of industrial robotic arms are deployed in repetitive tasks, the pose accuracy is much less of a key driver for the majority of consumers (e.g. the automotive industry) than speed, payload, energy efficiency and unit cost. Consequently, manufacturers of industrial robots often quote repeatability as an indication of performance whilst the pose accuracy remains comparatively poor. Due to their lack in accuracy, robotic arms have seen slower adoption in the aerospace industry where high accuracy is of utmost importance. However if their accuracy could be improved, robots offer significant advantages, being comparatively inexpensive and more flexible than bespoke automation.