UAV Uses Machine Learning to Carry out Perched Landing

The University of Bristol in the U.K. and BMT Defence Services (BMT), a subsidiary of BMT Group Ltd., have developed what they claim to be the first unmanned aerial vehicle (UAV) to perform a perched landing by using machine-learning algorithms.

The 18-month research project was delivered as part of the Defence Science and Technology Laboratory’s Autonomous Systems Underpinning Research program. BMT and Bristol University have demonstrated how the combination of a UAV and machine learning can be used to generate a trajectory to perform a perched landing on the ground.

The team’s primary goal was to look at extending the operation of fixed-wing UAVs by introducing morphing-wing structures inspired by those found in birds. To control these complex wing structures, BMT implemented machine-learning algorithms.

The development of a fixed-wing aircraft that can land in a small or confined space has the potential to significantly impact intelligence-gathering and the delivery of aid in a humanitarian disasters, according to the partners.

“Innovation is at the heart of everything we do at BMT, and R&D projects provide us with the opportunity to work with our partners to develop cutting-edge capabilities that have the potential to revolutionize the way we gather information,” comments Simon Luck, head of information services and information assurance at BMT Defence Services.


Please enter your comment!
Please enter your name here