A fleet of more than 100 robots are autonomously performing a range of important activities around Google facilities in the US, including as wiping tables, sorting trash, gripping cups, and even opening doors for visitors, signaling an era in which machines are slowly taking over human jobs.
Alphabet’s ‘Everyday Robots’ project — an unit under Google’s experimental X laboratories — has announced that several of its robot prototypes have been transported out of the lab and are doing useful duties throughout Google’s Bay Area facilities.
“We already have a fleet of more than 100 robot prototypes performing a variety of important activities around our headquarters,” Hans Peter Brondmo, Chief Robot Officer, said.
“The same robot that sorts trash can now be equipped with a squeegee to wipe tables and use the same gripper that grasps cups can learn to open doors,” he said in a statement.
Alphabet has spent the last few years developing an integrated hardware and software system for learning, including the transfer of knowledge from the virtual to the actual world.
To take in the world around them, the robots are outfitted with a variety of cameras and sensors.
“The robots have slowly gained a greater grasp of the world around them and become more adept at executing ordinary activities, using a combination of machine learning techniques like reinforcement learning, collaborative learning, and learning from demonstration,” according to the corporation.
Office workers in Mountain View may see the robot prototypes washing tables after lunch in cafés or opening meeting room doors to see whether the area needs to be tidied or if it is lacking chairs in the coming months.
“Over time, we will be expanding the types of tasks they are doing and the buildings where we operate and look forward to sharing updates from our journey over the coming months and years,” said Brondmo.
With less than a day of real-world learning, a single robot can now learn how to perform a complex task like opening doors with a 90% success rate.
“Even more exciting,” he continued, “we’ve demonstrated that we can take the algorithms and learnings from door opening and apply them to a new task: straightening up chairs in our cafes.” IANS
