Roboticists have developed many advanced systems over the past decade or so, yet most of these systems still require some degree of human supervision. Ideally, future robots should explore unknown environments autonomously and independently, continuously collecting data and learning from this data.
Researchers at Carnegie Mellon University recently created ALAN, a robotic agent that can autonomously explore unfamiliar environments. This robot, introduced in a paper pre-published on arXiv and set to be presented at the International Conference of Robotics and Automation (ICRA 2023), was found to successfully complete tasks in the real-world after a brief number of exploration trials.
“We have been interested in building an AI that learns by setting its own objectives,” Russell Mendonca, one of the researchers who carried out the study, told Tech Xplore. “By not depending on humans for supervision or guidance, such agents can keep learning in new scenarios, driven by their own curiosity. This would enable continual generalization to different domains, and discovery of increasingly complex behavior.”
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