Autonomous vehicles have been driving advances in vision technology, but vendors are targeting other practical applications because broad adoption of self-driving vehicles appears to be taking longer than expected.

Virtual reality (VR) and augmented reality (AR) both have need of improved cameras and sensors for practical use cases, while the trend toward “uncaging robots” for industrial applications such as warehouse fulfillment and manufacturing requires smarter vision technology, which spans 2D cameras to 4D LiDAR.

Layering artificial intelligence (AI), machine learning, and neural networks onto computer vision technologies further expands the many applications for a wide range of sensors and cameras.

Read my full story at Fierce Electronics.

Gary Hilson is a freelance writer with a focus on B2B technology, including information technology, cybersecurity, and semiconductors.