Universal robots master thesis

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Force controlled assembly process. In real and simulated environment. Work fast with our official CLI. Learn more. If nothing happens, download GitHub Desktop and try again. If nothing happens, download Xcode and try again.
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Robots Ph.D. Thesis Assistance - Writing a Master's Dissertation on Robots

The main objective of the follwing projects is to give students experience in working with advanced robotics tehcnology. Our main software platforms are Robot Operating System ROS for developing software for advanced robot systems and Gazebo for running realistic robotic simulations. A more detailed thesis topic will be outlined during in-person meeting. The objective of this thesis is to integrate robots available at the Institute of Technology in a single Gazebo simulation world to enable further software development and educational activities using these robots. Alternatively, this thesis could focus on creating a virtual reality representation of facilities and equipment at IMS-Robotics, e. Enhancing the user-experience of a virtual reality UI developed by Georg Astok. Potentially adding virtual reality capability to a gesture- and natural-language-based robot teleoperation system.
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"Robots" Dissertation Assistance, Writing Dissertations on "Robots," and PhD Dissertation Help

This program offers specialisations stemming from the overlap of three fields of research: Computer Science, Electrical Engineering and Mathematical Modelling. Each field represents an area where the application of software, data, computers and electronics has become necessary for the modern society, yet challenging to do in practice. These areas are wide enough to allow for life-long careers as technology progresses. Recent discoveries in artificial intelligence have enabled computers and machines to perform many cognitive tasks better than humans, from self-driving cars to diagnosing diseases in seconds.
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A model is developed using UNet with the help of Convolution Neural Networks that takes a chest x-ray image as input and predicts whether the given image has a pneumothorax or not. This environment makes use of a camera system equipped on the wrist of both the master and the slave robot, and uses OpenCV for detecting the contour of the target object. This information is then used by the RL agent for learning optimal policies for making both the robots reach the target. Two UR5 robots reach targets specified within their own workspace and coordinate at a common point using Reinforcement Learning. Designing an RL agent for the actuator of the PSM machine to reach the parcel position in the most optimum way.
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