Laundry-time data could power the next generation of home robots
Startups are turning videos of people doing chores (filmed by gig workers who can earn up to $25/hour) into training data for robot control software, using footage of laundry folding, dishwashing, and more to teach robots how to interpret sensor input and decide movements. The approach blends human videos, teleoperation, and simulated data to scale robot learning, a process that experts say is data-intensive and costly, with real-world deployment still years away.