Robots struggle to learn from each other, and rely on human instruction
New research from UC Berkeley shows that the process could be automated
This would eliminate the struggles of manually training robots
Despite robots being increasingly integrated into real-world environments, one of the major challenges in robotics research is ensuring the devices can adapt to new tasks and environments efficiently.
Traditionally, training to master specific skills requires large amounts of data and specialized training for each robot model – but to overcome these limitations, researchers are now focusing on creating computational frameworks that enable the transfer of skills across different robots.
