Machines are doing light janitorial work in the uncontrolled environment of Google’s offices.
What’s new: Everyday Robots, a new spin-out from Google’s experimental X Development division, unleashed 100 robots to perform an array of cleanup tasks. Since learning a few years ago to sort garbage for recycling, compost, and landfill, the machines have learned to open doors, straighten chairs, and squeegee tabletops (as in the video above).
How it works: The robot rolls on four wheels guided by lidar. Its head contains five cameras and other sensors whose output helps direct an articulated arm tipped with a gripping claw. Google implies that the control system uses a single base model and changes output layers for different tasks. It’s trained via imitation learning followed by rounds of reinforcement learning in conventional and federated learning (also called collaborative learning) settings.
- A human operator manipulates the arm to complete a task. A robot learns to imitate this behavior, sometimes in a simulation, sometimes in the real world.
- The robots refine such behaviors over large numbers of attempts in a simulation using reinforcement learning, which delivers a reward depending on how successful an attempt was.
- The robots share a cloud-based neural network that estimates the value of taking a given action in a given state. Each robot independently uses the network to decide what actions to take. Actions that garner rewards improve the neural network, and a new version is shared with the fleet at regular intervals.
- These steps prepare the robot to enter a real-world environment and achieve 90 percent success in a new task, such as opening doors, after less than one day of further federated learning.
Behind the news: Mechanical helpers are beginning to grasp basic custodial chores.
- Toyota Research Institute demonstrated a robot that performs rote house-cleaning tasks. It used machine learning to pick up objects without breaking them.
- Silicon Valley restaurants can send their dirty dishes to Dishcraft Robotics, where autonomous grippers guided by computer vision scrub a variety of plates and cutlery.
- The venerable Roomba is getting an AI makeover. The latest version of the robot vacuum cleaner can map rooms and avoid furniture.
Why it matters: In many countries, older people outnumber younger ones who could take care of them. Offices aren’t as complex as homes, with their clutter, tight spaces, and multi-story floor plans, but they are a proving ground for robots that might tidy up for people who aren’t able to do it themselves.
We’re thinking: We celebrate progress in robotics. At the same time, we empathize with people whose jobs are be threatened. Even as we build these wonderful contraptions, it’s important to provide workers with retraining, re-skilling, and safety nets to make sure no one is left behind.