AI system teaches robots how to navigate wilderness trails

Wilderness trail traversal is a useful skill for rescuers and outdoor enthusiasts alike, but one that's difficult to teach to robots. It's not that the mechanical beasts aren't capable of learning to hike up hillsides while avoiding fallen tree branches -- state-of-the-art machine learning algorithms can accomplish that much. The trouble lies in their lack of generalizability: AI-driven robots often struggle in environments they haven't seen before. Researchers at the University of Colorado recently proposed a solution in a paper ("Virtual-to-Real-World Transfer Learning for Robots on Wilderness Trails") published on the preprint server Arxiv.org. Their approach leverages a variety of deep learning models -- i.e., layers of neuron-simulating mathematical functions -- to help robots figure out the direction of hiking trails from camera footage.