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Why is it so hard to build profitable robot companies? Guest contributor Bram Vanderborght - May 7, 2019

Technology Alex Knight 199368 Unsplash Min 6B6997Fbc40F0De51D589Aa7564124C5

Roboticists need to openly and honestly discuss their successes as well as their failures.

In mid-November, we received the sad news that Alphabet is closing SCHAFT, a spinoff of the University of Tokyo robotics lab. The decision comes one year after Boston Dynamics was sold to SoftBank, the company that also acquired Aldebaran Robotics (known for the Pepper and Nao robots). During the 2018 IEEE/Robotics Society of Japan International Conference on Intelligent Robots and Systems, we heard that Rethink Robotics, which created the collaborative robot industry and had a large impact on our view of robots in industrial applications, had closed its doors.

Some months before, Jibo and Mayfield Robotics, makers of Kuri, were forced to shut down sales and operations. Jibo was once heralded as “the first social robot for the home” and was named one of Time’s “Best Inventions of 2017.” Other than a few robot vacuum companies (mainly iRobot), no company has developed a successful home robot.

Late last year, Jibo shut down its Boston office and completed the sale of its assets and intellectual property to a New York–based investment management firm.

The news initiated a discussion on Facebook among robotics leaders, such as Chris Atkeson from Carnegie Mellon University’s Robotics Institute; James Kuffner, chief executive officer of the Toyota Research Institute - Advanced Development (TRI-AD); and Giulio Sandini from the Italian Institute of Technology. All agree the robotics industry is still on the rise; it is just extremely hard to make a profitable robotics company. But, unless big bets are made, new research and technology will never mature into products that are practical and useful for the world. Moreover, success in this area demands more than good technology. As James Kuffner stated, “It requires significant funding, committed leadership, highly skilled staff, resources, and infrastructure, and an excellent product and market strategy. Not to mention flawless execution. It is unrealistic to expect every effort to succeed.”

Overselling is a dangerous strategy that can be counterproductive. Both companies and researchers publish videos of robots doing tasks, but sometimes they fail to point out the limitations of the technology or that those results were achieved in lab conditions.

Chris Atkeson raised the big questions: What have we learned from the failures? How can we further build on the work? What lessons can be taken? How will the intellectual property be transferred? The future will tell whether the know-how will be reincarnated. Often, the work is secret, especially when sponsored by the military, and only amazing YouTube videos are released. However, some companies choose to contribute to the open source movement, with the Robotic Operating System (ROS) as probably the most well-known example.

Moreover, the investments of tech giants in robotics and artificial intelligenceenergized and catalyzed the industry, resulting in billions of dollars of additional investment in research and development around the world. Hopefully, companies will also publish—e.g., in IEEE journals and magazines—more scientific insights on their products.

Rethink Robotics, a startup founded by Rodney Brooks to develop collaborative robots, closed its doors last October.

The problem, as Giulio Sandini put it, occurs when one sells (or buys) intentions as results. Overselling is a dangerous strategy that can be counterproductive, even for the whole robotics community. Both companies and researchers publish videos of robots doing tasks, but sometimes they fail to point out the limitations of the technology or that those results were achieved in lab conditions. This makes it much more difficult to explain to nonroboticist industry executives the difference between creating a one-off demo and creating a real product that works reliably.

Deep learning, for example, is at the forefront of the AI revolution, but it is too often viewed as the magic train carrying us into the world of technological wonders. AI researchers are warning about overexcitement and that the next AI winter is coming.

The first cracks are already visible, as is the case of the promises claimed for self-driving cars. Rodney Brooks, founder of Rethink Robotics, regularly writes relevant essays on this topic on his blog. Robot ethics professor Noel Sharkey wrote an article in Forbes titled “Mama Mia It’s Sophia: A Show Robot or Dangerous Platform to Mislead?Tony Belpaeme, a social robot researcher from the University of Ghent, replied with a tweet, “I had [a European Union] project reviewer express disappointment in our slow research progress, as the Sophia bot clearly showed that the technical challenges we were still struggling with were solved.”

It is our common responsibility and interest to disseminate openly and honestly not only our success but also our failures. Together, we can realize our dreams for numerous robotic applications and devise a realistic plan to develop them.

A version of this article appeared in the IEEE Robotics & Automation Magazine (Volume 26, Issue 1, March 2019) and in IEEE Spectrum, one of the world's leading engineering magazines.

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Guest contributor Bram Vanderborght

Bram is a professor in robotics at the Vrije Universiteit Brussel. He is focussed on developing a new generation of robots that will physically and socially support humans in the...

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