top of page

Robust Autonomous Drone Landing

Researching key innovations in Sensor Fusion, Machine Learning & AI, Formal Methods, and Computer Vision to deliver a fully autonomous system capable of landing safely in uncontrolled environments without the supervision of a pilot or trained personnel.

The aim of this ARC Linkage Project is to collaborate between industry and academia to develop a novel robust and scalable autonomous landing solution for drones.  One of the biggest issues facing drone delivery today is the last meter problem, namely that there are many challenging corner cases that make it complex and difficult to reason about what is a safe landing site for a drone to deliver a package.  This proposal will apply machine learning to train robust and intelligent algorithms to recognize using sensor data in what situations it is safe to deliver a package. Robust validation of a solution will be performed throughreal world flight tests with drones.  Finding a solution to this problem will surmount a difficult technical challenge that even the top technical companies have yet to fully solve, and spur Australia towards pioneering large scale delivery of items using drones.  This project is a partnership between ARC, Macquarie University and Skyynet, Inc., an Australia-based drone company.


Prof. Richard Han, Prof. Annabelle Mclver, Dr James Zheng, Prof Subhas Mukhopadhyay, Dr. Endrowedness Kuantama, Yao Deng, Avishkar Seth, Alice James, Linfeng Liang, Jiaohong Yao, Yihao Zhang


Skyy Network

Project Gallery

bottom of page