News & Events


Rapid Adaptation of Deep Learning Teaches Drones to Survive Any Weather


To be truly useful, drones—that is, autonomous flying vehicles—will need to learn to navigate real-world weather and wind conditions. A team of engineers from Caltech has developed Neural-Fly, a deep-learning method that can help drones cope with new and unknown wind conditions in real time just by updating a few key parameters. [Caltech story]

Tags: research highlights GALCIT CMS Yisong Yue Soon-Jo Chung Animashree Anandkumar Xichen Shi Guanya Shi Michael O'Connell Kamyar Azizzadenesheli

Machine Learning Helps Robot Swarms Coordinate


Soon-Jo Chung, Bren Professor of Aerospace, Yisong Yue, Professor of Computing and Mathematical Sciences, postdoctoral scholar Wolfgang Hönig, and graduate students Benjamin Rivière and Guanya Shi, have designed a new data-driven method to control the movement of multiple robots through cluttered, unmapped spaces, so they do not run into one another. "Our work shows some promising results to overcome the safety, robustness, and scalability issues of conventional black-box artificial intelligence (AI) approaches for swarm motion planning with GLAS and close-proximity control for multiple drones using Neural-Swarm," says Chung. [Caltech story]

Tags: research highlights GALCIT CMS Yisong Yue CNS Soon-Jo Chung postdocs Benjamin Rivière Guanya Shi Wolfgang Hönig