Humans and animals move with remarkable economy without consciously thinking about it by utilizing the natural oscillation patterns of their bodies. A new tool can now utilize this knowledge for the first time to make robots move more efficiently.
Four-legged animals that start walking and gradually pick up speed will automatically fall into a trot at some point. This is because it would take more energy not to change gait. This correlation was discovered more than 40 years ago. Now, Alin Albu-Schäffer, a professor at the Chair of Sensor-based Robotic Systems and Intelligent Assistance Systems at TUM, has successfully transferred this method to the movement of robots.
An important test object in the team's research is BERT, a four-legged robot that looks like a small dog. BERT was designed by Prof. Albu-Schäffer at the German Aerospace Centre . The research, which focuses on"efficient and versatile locomotion with legs," is funded by the EU through an ERC Advanced Grant.
Success is demonstrated in a race between three BERT models. The robot dog, which has been programmed with the intrinsic movement method, tends to jump and move much faster and more dynamically than its siblings, which rely on more conventional movement patterns. New algorithm encourages robots to move more randomly to collect more diverse data for learning. In tests, robots started with no knowledge and then learned and correctly performed tasks within a ...
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