Pairing human demonstrations with simulation for robot learning
A post highlighting UC Berkeley work argues that visual imitation followed by trial and error is a good recipe for robots—and questions where that leaves teleoperation.
TLDR
A post sharing UC Berkeley work says it shows the power of combining two sources of robot-learning data: humans performing tasks themselves and robots acting in simulators. The author compares visual imitation followed by trial and error to how children learn. They also identify teleoperation—humans remotely controlling robots—as a popular data source, then ask where it fits.
Pairing human demonstrations with simulation for robot learning
A post highlighting UC Berkeley work argues that visual imitation followed by trial and error is a good recipe for robots—and questions where that leaves teleoperation.