Project CETI and Harvard have established a new reinforcement learning framework for rendezvous with whales using autonomous robots, combining sensing from diverse sensor streams.
Project CETI and Harvard have established a new reinforcement learning framework for rendezvous with whales using autonomous robots, combining sensing from diverse sensor streams.
Project CETI (Cetacean Translation Initiative) aims to collect millions to billions of high-quality, highly contextualized vocalizations in order to understand how sperm whales communicate. But finding the whales and knowing where they will surface to capture the data is challenging — making it difficult to attach listening devices and collect visual information.
Today, a Project CETI research team led by Stephanie Gil, Assistant Professor of Computer Science at the Harvard John A. Paulson School of Engineering and Applied Sciences (SEAS), have proposed a new reinforcement learning framework with autonomous drones to find sperm whales and predict where they will surface.
The research is published in Science Robotics.
Read more at Harvard John A. Paulson School of Engineering and Applied Sciences
