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.

LEAVE A REPLY

Please enter your comment!
Please enter your name here