Researchers investigated how robotic systems can adapt their propulsion mechanisms in response to damage, drawing inspiration from how fish and insects adjust their movement when injured. They tested a flapping robot in a tank of oil, which was chosen for its superior signal-to-noise ratio compared to water. After amputating a portion of the robot’s flapper, they employed machine learning to help the robot adapt its propulsion mechanism.
Without help, the robot’s damaged flapper would have made it unable to move. However, by incorporating bioinspired adaptation techniques, the robot was programmed to experiment with various stroke mechanics. The system ran multiple trials to determine which mechanics allowed the robot to move efficiently despite the damage. Through machine learning algorithms, the robot refined its movement patterns, achieving effective propulsion even with 50 percent of its flapper removed.
More information:
https://interestingengineering.com/science/robot-adapts-damage-bioinspired-techniques