Obstacle avoidance by a drone (VIDEO) Princeton University, Engineering School This video is under embargo. Please login to access this video. To view this video please enable JavaScript, and consider upgrading to a web browser that supports HTML5 video Caption Princeton researchers adapted machine learning frameworks from other arenas to the field of robot locomotion and manipulation, applying generalization theory to the complex task of making guarantees on robots' performance in unfamiliar settings. In a proof of principle, the researchers validated the technique by assessing the obstacle avoidance of a small drone called a Parrot Swing as it flew down a 60-foot-long corridor dotted with cardboard cylinders. The guaranteed success rate of the drone's control policy was 88.4%, and it avoided obstacles in 18 of 20 trials (90%). Credit Intelligent Robot Motion Lab at Princeton University Usage Restrictions Noncommercial use only License Licensed content Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.