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|Title:||Development of an autonomous airborne docking and undocking system for micro drones to a mother drone||Authors:||Showers, Inyeni Amakuro||Issue Date:||2019||Publisher:||Cape Peninsula University of Technology||Abstract:||This work covers the concept and algorithms for an autonomous quadcopter (micro drone) to deploy from a docked position on a vertical take-off and landing (VTOL) drone, which is the mother drone (AMTL Guardian 4). The deployed quadcopter then returns autonomously to its initial docked position after completing a mission. This airborne docking system allows for refuelling or assigning another mission to the micro drone after successful docking. The mother drone is modelled as an autonomous ground station using the Pitsco education robotics kit. A docking arm mechanism mounted on the mother drone provides a platform for docking the micro drone and a grabbing mechanism for holding the docked drone in position. The micro drone is a DJI tello drone. It is programmed using the DJI tello python SDK. OpenCV, an open source python based computer vision library is used to implement object detection and tracking on the micro drone. For the ground station, LabVIEW Vision Acquisition and Vision Assistant are used to develop object detection and tracking algorithms for the docking system. An algorithm tagged as the hand-shake docking algorithm is used to coordinate autonomous movements in the mother drone and micro drone to achieve docking and undocking of the micro drone from the mother drone. It is projected that this research will advance current drone technology and create increasing interest on research towards autonomous airborne docking systems.||Description:||Thesis (MEng (Mechanical Engineering))--Cape Peninsula University of Technology, 2019||URI:||http://hdl.handle.net/20.500.11838/3161|
|Appears in Collections:||Mechanical Engineering - Master's Degree|
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