Over the past decades, roboticists have introduced a wide range of systems with distinct body structures and varying capabilities. As the number of developed robots continuously grows, being able to easily learn about these many systems, their unique characteristics, differences and performance on specific tasks could prove highly valuable.

Researchers at Technical University of Munich (TUM) recently created the “Tree of Robots,” a new encyclopedia that could make learning about existing robotic systems and comparing them significantly easier. Their robot encyclopedia, introduced in a paper published in Nature Machine Intelligence, categorizes robots based on their performance fitness on various tasks.

“The aspiration for intelligent robots that can understand their environment as we humans do, and execute tasks independently, has existed for ages,” Robin Jeanne Kirschner, first author of the paper, told Tech Xplore.