UPDATE: New video of a collaborative, cloud-based mapping experiment. Mapping is essential for mobile robots and a cornerstone of many more robotics applications that require a robot to interact with its physical environment. It is widely considered the most difficult perceptual problem in robotics, both from an algorithmic but also from a computational perspective. Mapping essentially requires solving a huge optimization problem over a large amount of images and their extracted features. This requires beefy computers and high-end graphics cards – resulting in power-hungry and expensive robots.

Cloud robotics, a shorthand for the idea of leveraging the Internet for robots, offers unprecedented opportunities for robot learning. Apart from using the World Wide Web for faster communication or faster computation, a key opportunity is to allow robots to create and collaboratively update shared knowledge repositories. Hosted in a shared cloud storage infrastructure, such knowledge bases for robots could enable robots to cope with the complexities of human environments and offer a simple, powerful way for life-long robot learning.