Robotics»
Robot co-active learning adjusts to context-driven user preferences
Researchers at the Cornell University created an algorithm which enables robots to “coactively learn” from humans and make adjustments while an action is in progress. Their approach relies on a combination of machine learning, object and user association, and trajectory adjustment could allow robots to operate more reliably when it comes to object manipulation and… »