The Hardest Challenge in the Field of Robotics
Today, robots are expensive and perform highly specialized tasks. But what if a robot could be affordable and taught by just about anyone? They could help people with whatever they needed, doing tasks we haven't even dreamed up yet.
Building robots that can operate autonomously in unstructured human environments, like our homes and offices, is a complex, unsolved problem. It requires tackling and integrating some of the hardest hardware and software challenges in the field of robotics today. The Everyday Robots team was working to create a general-purpose learning robot that could operate autonomously in unstructured environments. Their mission was to build a new type of learning robot — one that can eventually learn to help everyone, every day.
Robots That Can Help in Everyday Environments
Today, most robots operate in environments specifically designed and structured for them. The tasks they complete are very specific, and robots need to be painstakingly coded to perform those tasks in exactly the right way, at exactly the right time. As a result, robots are incapable of adapting to the unpredictable and unstructured nature of everyday life.
The Everyday Robot Project focused on making robots to safely operate in human environments, where things change every day, people show up unexpectedly, and obstacles appear out of nowhere. In order for robots to be useful day, they need to understand and make sense of the spaces where we live and work, and adapt to them as they gain experience. This requires new forms of machine intelligence.
High-fidelity simulations of virtual everyday environments enabled everyday robots to practice and learn quickly.
Detecting objects played a critical role in helping everyday robots navigate and interact within our everyday environments.
Cameras in the robot's head and sophisticated machine learning models helped our robots see and understand the world.
An arm on the robot helps it grasp, move, and interact with all kinds of everyday objects.