Alphabet Inc. on Friday, the 19th of November 2021 announced the deployment of multi tasker robots into its Google U.S offices to be used for different purposes.
The Google parent company in its latest innovative move would make the machines perform actions like assisting humans on daily basis.
Alphabet innovation team, X affirmed that the robots have reached the requisite level to operate autonomously at the search engine’s headquarters, Mountain View, California.
This was corroborated by a statement by Chief Robot Office (CRO) for Everyday Robots, Hans Peter Brøndmo when he said:
“The same robot that sort’s trash can now be equipped with a squeegee to wipe tables and use the same gripper that grasps cups can learn to open doors”.
The multi tasker robots will have the capacity to concurrently perform various tasks, an advantage over the traditional robots. The major goal of the team that developed the machines is to make the robots learn from its tasks by extracting the process of forcing developers to constantly program it to conduct a specific chore under certain conditions.
“Imagine trying to script all the possible ways to pick up a cup of coffee, anticipate the lighting, or open a door. It simply wouldn’t scale,” Brøndmo added.
The cyborg innovation raises questions on how it will be effectively managed prompting the Division X team of developers implement machine learning algorithms that would help train the robots to accomplish a chosen goal through repetitive trial and error simulations.
Before the application of its knowledge in the real world, the use of Everyday Robots machinery will be executed with pulling through a specified task in a 3D simulation.
The 3D stimulation incorporation procedure with machine learning algorithms will intrinsically reduce the hassles of periodically training the robots to perform these tasks.
“Back in 2016, when we weren’t using simulation and were using a small-lab configuration of industrial robots to learn how to grasp small objects like toys, keys and everyday household items, fit took the equivalent of four months for one robot to learn how to perform a simply grasp with a 75 percent success rate,” Brøndmo stated.
One other advantage is the robot’s augmented ability to learn a single task, while reapplying it to achieve another goal. But it can only be possible when the robot is trained to use algorithmic and learnings behaviour to complete many tasks, simply by mirroring a previous one.
The Division X team at Aphabet has already started the deployment of these multi tasker robots across Google’s office based in the San-Francisco Bay area, with the team now focused on suitable training the robots to learn new tasks to assist the company’s employees.