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Full-Text Articles in Engineering
Brian Valdez - Dynamics And Control Of A 3-Dof Manipulator With Deep Learning Feedback, Brian Orlando Valdez
Brian Valdez - Dynamics And Control Of A 3-Dof Manipulator With Deep Learning Feedback, Brian Orlando Valdez
Open Access Theses & Dissertations
With the ever-increasing demands in the space domain and accessibility to low-cost small satellite platforms for educational and scientific projects, efforts are being made in various technology capacities including robotics and artificial intelligence in microgravity. The MIRO Center for Space Exploration and Technology Research (cSETR) prepares the development of their second nanosatellite to launch to space and it is with that opportunity that a 3-DOF robotic arm is in development to be one of the payloads in the nanosatellite. Analyses, hardware implementation, and testing demonstrate a potential positive outcome from including the payload in the nanosatellite and a deep learning …
Remote Control Of Multiple Robots: A Wireless Sensor Network And Virtual Reality Approach, Yingjun Zhu
Remote Control Of Multiple Robots: A Wireless Sensor Network And Virtual Reality Approach, Yingjun Zhu
Open Access Theses & Dissertations
A tele-operation system of robots based on virtual reality and WSN is established and demonstrated. Pro/E, Blender 3D and Python language are adopted to build up and carry out the virtual environment and virtual robot. Wireless Sensor Network (WSN) technology has been used to achieve the tele-operation function. The WSN enables the users to control the robots and collect the data/status from the robots as well. Robot virtual reality software has been developed and presented in the paper. The network setup and the control/communication Application Programming Interface (API) has been shown in this paper.
E-Quality Control: A Support Vector Machines Approach, Kalyan Reddy Aleti
E-Quality Control: A Support Vector Machines Approach, Kalyan Reddy Aleti
Open Access Theses & Dissertations
The web-enabled quality control process presents many benefits to industry, such as universal access, remote control capability, and integration of production equipment into information networks for improved efficiency. This capability has a great potential, since engineers can access and control the equipment anytime, anywhere as the design stages evolve. In this context, this work uses innovative methods in remote part tracking and quality control with the aid of the modern equipment and application of Support Vector machine learning approach to predict the outcome of the quality control process. The classifier equations are built on the data obtained from the experiments …