Tesla Is Patenting AR Smart Glasses

A Tesla production site. (Image courtesy of Tesla.)

While the future of transportation may be unknown, getting there will require manufacturing innovations. Paving the way for change is Tesla. The company—known for electric and autonomous cars, among other things—has its eye on using augmented reality (AR) to make such innovations happen. The company recently applied for two AR patents for smart glasses that can be used by humans and robots. In addition to doing doubly duty as safety glasses, these devices would assist with quality assurance.

The driving force behind the technology is time. From design to construction, the process of manufacturing automobiles is a long one that requires extensive manual calibration and inspection. It takes time to program and position robots, to mark the placement of mechanical joints, and to set up, configurate, calibrate and inspect parts. Every step that requires extra time means added product costs.

According to the patent application, “There exists a need for a process and tools for increasing the efficiency and decreasing the cost of automotive manufacturing tasks. Applying computer vision and augmented reality tools to the manufacturing process can significantly increase the speed and efficiency related to manufacturing and in particular to the manufacturing of automobile parts and vehicles.”

Tesla’s vision for AR smart glasses will help speed up production while also ensuring quality. (Image courtesy of Tesla.)

The use of AR technology would help speed up the manufacturing process by reducing human error and enhancing quality control. AR reference markers—such as a sticker, QR code or radio frequency—would be created to overlay associated digital data over what was in front of an item on the line, even as the item was moved around. For example, if a worker was looking at a shock tower, the AR device would detect this and provide data related the tower’s features.

This could help workers detect things like correct weld or drill locations, seals and tolerances. For example, the glasses could help with identifying any issues. The data would include assembly details, such as weld order or type of weld, further ensuring that tasks are completed correctly and in order.

The devices are also being designed to assist with programming robots for enhanced assembly. As for the robots, the glasses have the potential to be another potential tool for quality control checks.