Visual Servo Based Space Robotic Docking for Active Space Debris Removal

This thesis developed a 6DOF pose detection algorithm using machine learning capable of providing the orientation and location of an object in various lighting conditions and at different angles, for the purposes of space robotic rendezvous and docking control. The computer vision algorithm was paired with a virtual robotic simulation to test the feasibility of using the proposed algorithm for visual servo. This thesis also developed a method for generating virtual training images and corresponding ground truth data including both location and orientation information. Traditional computer vision techniques struggle to determine the 6DOF pose of an object when certain colors or edges are not found, therefore training a network is an optimal choice. The 6DOF pose detection algorithm was implemented on MATLAB and Python. The robotic simulation was implemented on Simulink and ROS Gazebo. Finally, the generation of training data was done with Python and Blender

Bis(fluorosulphuryl)imide derivatives of zinc(II), cadmium(II), mercury(II) and their coordination complexes with oxygen and nitrogen donors

890-892Bis(fluorosulphuryl)imides of zinc(II) and cadmium(II), [M{N(SO2F)2}2], have been prepared in > 90% yield by reacting the metal trifluoroacetates with excess bis(fluorosulphuryl)imide in trifluoroacetic acid medium. These compounds and [Hg{N(SO2F)2}2], which has been prepared by a known method, have been characterized by their elemental analyses and infrared spectral data. These are found to be thermally stable up to 200°C and are insoluble in non-coordinating solvents and HN(SO2F)2. These form coordination complexes of the type [M(L)x{N(SO2F) 2}2] where M = Zn(II), Cd(II) and Hg(II); x = 4, L = pyridine, acetonitrile and triphenylphosphine oxide; x = 2, L= 2,2'-bipyridyl