The position is now filled.
We are pleased to announce that Cyber-Human Lab (CHL) will offer another summer research internship under the Undergraduate Research Opportunities Programme (UROP). The project will be carried out under the supervision of CHL’s Dr Sławomir Tadeja and Dr Thomas Bohné in collaboration with Dr Przemysław Konrantowski, the founder of Aerial Robotic Systems Lab at Warsaw University of Technology. Dr Kornatowski holds a PhD in Robotics, Control, and Intelligent Systems (2020) from the Laboratory of Intelligent Systems, École Polytechnique Fédérale de Lausanne (EPFL), and was also one of the original contributors working on a reconfigurable drone system for transporting parcels with variable mass and size (IEEE RA-L 2022, doi: 10.1109/LRA.2022.3208716).
The UROP opportunity is restricted to Cambridge/CUED undergraduates only. If interested, please send your CV and application to Dr Sławomir Tadeja (skt40@eng.cam.ac.uk).
This opportunity is supported by the award from MathWorks-CUED Small Grant Programme 2024. We are thankful to the MathWorks and Grant Committee Members for bestowing us this grant.
Project: Using Augmented Reality for Guiding Assembly of Reconfigurable Multicopter System Delivering Parcel
Traditional parcel delivery drones struggle with adaptability, requiring a dedicated fleet for diverse package weights and sizes. To address this limitation, a novel reconfigurable multicopter system has utilised a modular design where the parcel serves as the drone’s body. Individual propulsion modules are readily attached to designated docking points on the parcel’s surface. Thanks to such an approach, a single drone solution can now transform to accommodate an array of parcel dimensions and weights, eliminating the need for a specialized fleet and fostering resource efficiency. However, efficient deployment of these modules presents a new challenge. To streamline the attachment process and reduce errors, we plan to prepare an Augmented Reality (AR) interface facilitated by a specialised headset. Such an approach warrants free, unconstrained hand movement while providing a standalone edge computing platform that we can use to guide drone placement and attachment.
The expected outcome is an Augmented Reality (AR) demonstrator deployed on a pre-selected drone payload. The demonstrator will be equipped with technical documentation and instruction video distributed together with the developed source code in the form of an open-source remote repository on the GitHub platform. Moreover, part of the package will be a PowerPoint presentation describing the step-by-step design engineering process to develop our demonstrator system. Prior knowledge of Matlab is desired.
