faster than you might think

faster than you might think

Robots are making their first tentative steps from the factory floor into our homes and workplaces. In a recent report, Goldman Sachs Research estimates that a $6 billion market (or more) could be achieved in robots the size and shape of people in the next 10 to 15 years. Such a market would be able to fill 4% of the projected US industrial labor shortage by 2030 and 2% of the global demand for aged care by 2035.

GS Research is projecting a more ambitious add-on, too. The authors of the report, “Investing Case for Human bots. A market of this size could fill from 48% to 126% of the labor gap, and up to 53% of the elderly caregiver gap.

Hurdles remain: Today’s humanoid robots can only run in short bursts of an hour or two before needing to recharge. The research says that some humanoid robots have mastered movements and agility, while others can handle cognitive and intellectual challenges — but none can do both. One of the most advanced robot-like technologies on the commercial market is an autonomous vehicle, but a humanoid robot would have to have intelligence and processing capabilities greater than that — by an order of magnitude. “In the history of the development of humanoid robots, no robots have yet been successfully commercialized,” the report says.

However, there is a way for humanoid robots to become smarter and more affordable than new electric cars. Goldman Sachs suggests that humanoid robots could be economically viable in factory settings between 2025 and 2028, and in consumer applications between 2030 and 2035. Several assumptions support this prediction, and the Goldman Sachs Research report details the multiple breakthroughs that need to happen for this to come about. fruits.

  • The battery life of humanoid robots should improve to the point where one can run for up to 20 hours before requiring a recharge (or need a one-hour fast charge and run for four to five hours, then repeat).
  • Mobility and agility should increase incrementally, and the processing capabilities of such robots should see steady gains. In addition, depth and feedback cameras, visual and acoustic sensors, and other aspects of sensing — the robot’s nerves and sensory organs — will all need to improve incrementally.
  • You’ll also need to gain arithmetic, so that the bots can avoid obstacles, carve out the shortest path to complete a task, and answer questions.
  • The biggest challenge remains the process of training and improving the capabilities of humanoid robots once they start working. This process can take up to a year.
  • Finally, robot makers will need to cut production costs by about 15-20% per year in order for the robot to pay for itself in a couple of years.

These challenges may seem daunting but there is precedent to work through. The report builds on the experience of factory collaborative robots – or “cobots” – that are now part of manufacturing centers such as car factories. It took about seven to 10 years for it to go from its first commercially available release to batch sales. They faced, as bots do now, great skepticism.

And like robots that still struggle today, it had a lot to learn in terms of dexterity and responsiveness. But today, bots are becoming commonplace in some industrial applications, and humanoid robots could find a place, too. “Robotic robotics solutions could also be attractive in areas that large industrial robot makers have difficulty servicing,” the report states, “including the realm of warehouse management/logistics management and simple areas with a heavy human load, such as moving goods up and down stairs.” “.

In a home environment, the scope of the challenges would be much more complex. “It is much more difficult to design consumer/home applications due to more diverse application scenarios, diverse object recognition, more complex navigation system, etc,” says the report. This brushes aside how ordinary people interact and respond to humanoid robots themselves. “There are many other issues to consider, including disputes surrounding the replacement of human operators, the trust and safety, the privacy of the data they collect, their similarity to actual humans, the inability to truly replace human emotions, issues around brain-computer interaction, and the ethics of their autonomy. “.


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