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.
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.
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.
