How iRobot used data science, cloud, and DevOps to design its next-gen smart home robots

In this blog, I will talk about iRobot used data science, cloud to design smart rooms. Watching iRobot’s new vacuum tag-team with the company’s latest robot mop to clean a room is to glimpse a Jetsons-like orchestration of the home of the future. Perhaps no company is as synonymous with robot vacuums as iRobot. To date, the Bedford, Massachusetts-based firm has sold more than 25 million units to customers around the world, and it has an estimated 88% share of the robot vacuum market.

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The core item in the new design language is the circle in the middle of the robots. The circle represents the history of iRobot, which featured a bevy of round Roomba robots. “The circle is a nod back to the round robots and gives us the ability to be more expansive with geometries.

For a glimpse into iRobot’s fascinating history:

– 1998: iRobot developed military robots under a DARPA research contract.
– 2001: iRobot’s PackBot military robot searches at World Trade Center after Sept. 11 terrorist attacks.
– 2002: Roomba launched.
– 2005: iRobot went public.
– 2012: iRobot acquired Evolution Robotics, which made automated floor mopping robots.
– 2016: iRobot sold its military robot business to Arlington Capital Partners and the unit becomes Endeavor Robotic Holdings, which was acquired by FLIR Systems in 2019 for $385 million.
– 2016: iRobot launches Braava jet mopping robot.
– 2018: iRobot launches Roomba i7+ with Clean Base Automatic Dirt Disposal and ability to store maps.

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Everybody wanted to have a robot that would climb up the stairs like a human, but that costs 1,000 times more and is 10 times slower than what we did with treads. The mental image of how robots are going to vacuum was a humanoid pushing a manual upright vacuum, and that’s so profoundly wrong on many levels. It’s just about the most complicated, expensive way of creating a robot vacuum you can possibly imagine.”  The two-wheeled, disc-shaped autonomous vacuum can detect the presence of obstacles and sense steep drops (with cliff sensors) to keep it from falling down stairs or off tall balconies.

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I hope you like this blog, How iRobot used data science, cloud, and DevOps to design its next-gen smart home robots.

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