Will 2025 be the year of the public-facing workplace robot?
It’s something operators want to happen in the coming year, The Wall Street Journal (WSJ) reported Tuesday (Dec. 31).
The robotics/drone industry had drawn in roughly $12.8 billion in venture capital funding by mid-December, the report said, citing PitchBook data. That’s compared to the $11.6 billion the sector attracted for the whole of 2023.
But while robot-makers are excited about what generative artificial intelligence (GenAI) can do for their product, they acknowledge that robots may take some time to interact with humans without some hiccups, the WSJ said.
“Some things which are very easy for people are very hard for robots,” said David Pinn, CEO of Brain Corp, which makes software for automated floor-cleaning and inventory management robots used by retailers such as Sam’s Club.
Even a task as simple as picking up a random object and moving it “is a really hard problem in the world of robotics,” he said.
And at Houston Methodist health system, Chief Innovation Officer Roberta Schwartz learned that the robots used to do things like check fire extinguishers and deliver towels were confused by elevators and tended to bump into objects.
The report notes that robotics that will work alongside with people will need better dexterity and the ability to get around obstacles — both issues that generative AI can help solve.
“You can train the robot through massive data sets to be able to achieve this kind of dexterity, that until now has only been achievable by our own labor,” said Brain Corp’s Pinn.
PYMNTS explored this issue earlier this month after researchers at MIT debuted PRoC3S, a new AI system that could help warehouse robots handle oddly-shaped packages and more effectively navigate crowded spaces.
The system melds AI language models with computer vision and tests actions in a virtual environment before carrying them out them, completing basic tasks like drawing shapes and sorting blocks with 80% accuracy during lab tests. PRoC3S aims to help robots perform complicated warehouse jobs that normally require human dexterity.
“In theory, PRoC3S could reduce a robot’s error rate by vetting its initial LLM-based assumptions against more specific and accurate understandings of the warehouse environment,” Erik Nieves, CEO and co-founder at Plus One Robotics, told PYMNTS.
“Think about it like this: A warehouse robot operating solely on LLM guidance has been described how to complete a task. The PRoC3S concept goes one step further by placing a digital robot in a simulated environment of that task. It’s essentially the difference between classroom instruction and a really good field trip.”
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