Drones Navigate Unseen Environments with Liquid Neural Networks

MIT researchers exhibited a new advancement in autonomous drone navigation, using brain-inspired liquid neural networks that excel in out-of-distribution scenarios. In a series of quadrotor closed-loop control experiments, the drones underwent numerous tests (ranges, stress, target rotation, and more); watch this video to see how they fared.

“We are thrilled by the immense potential of our learning-based control approach for robots, as it lays the groundwork for solving problems that arise when training in one environment and deploying in a completely distinct environment without additional training,” says Daniela Rus , CSAIL director and the Andrew (1956) and Erna Viterbi Professor of Electrical Engineering and Computer Science at MIT.