"Robot Learning Takes Cues from Human Toddlers"
Researchers are exploring new approaches to robot learning inspired by human toddlers. Carnegie Mellon University (CMU) has developed RoboAgent, a robotic AI agent that combines passive learning (teaching a system through videos and datasets) with active learning (performing tasks and adjusting). The system can learn from one environment and apply the knowledge to another, similar to CMU's Vision-Robotics Bridge (VRB) system. The dataset used is open source and compatible with off-the-shelf robotics hardware, making it accessible for researchers and companies. The goal is to create multipurpose robots that can adapt and learn in unstructured settings like homes and hospitals.