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1. Design and initial performance of the HARDWARE.astronomy Housekeeping (H.aHk) box

   https://doi.org/10.1117/12.2630261  

   Shaw, Stephen ; Vettleson-Trutza, Larry ; Ferkinhoff, Carl ; Stammer, Adam ; Antwi, Nathan ; Kovacevich, Aubrey ; Franta, Alex ; Stacey, Gordon J. ; Nikola, Thomas ; Rooney, Christopher ; et al ( August 2022 , Proc. SPIE 12190, Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy XI)

   Zmuidzinas, Jonas ; Gao, Jian-Rong (Ed.)

   An often unglamorous, yet critical, part of most millimeter/submillimeter astronomical instruments is cryogenic temperature monitoring and control. Depending on the operating wavelength of the instrument and detector technology, this could be stable temperatures in the Kelvin range for millimeter heterodyne systems to 100 mK temperatures at sub-micro-Kelvin stability as for many submillimeter bolometer systems. Here we describe a project of the HARDWARE.astronomy initiative to build a low-cost open-source temperature monitoring and control system. The HARDWARE.astronomy Housekeeping Box, or H.aHk Box (pronounced “hack box”) is developed primarily by undergraduates and employs existing open-source devices (e.g Arduino, Raspberry Pi) to reduce costs while also limiting the complexity of the development. The H.aHk Box features a chassis with a control computer and ten expansion slots that can be filled with a variety of expansion cards. These cards include initially an AC 4-wire temperature monitor and PID control cards. Future work will develop 2-wire temperature monitors, stepper motor controller, and high-power supply. The base-system will also be able to interface with other house-keeping systems over USB, serial port and ethernet. The first deployment of the H.aHk Box will be for the ZEUS-2 submillimeter grating spectrometer. All designs, firmware, software and parts list will be published online allowing for other projects to adopt the system and create custom expansion cards as needed. Here we describe the design (including mechanical, electrical, firmware, and software components) and initial performance of the H.aHk Box system with initial AC/DC 4-wire and PID cards. 

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2. An Energy Shaping Exoskeleton Controller for Human Strength Amplification

   Thomas, Gray C. ; Gregg, Robert D. ( January 2021 , Proceedings of the IEEE Conference on Decision Control)

   null (Ed.)

   In this work, we introduce a novel approach to assistive exoskeleton (or powered orthosis) control which avoids needing task and gait phase information. Our approach is based on directly designing the Hamiltonian dynamics of the target closed-loop behavior, shaping the energy of the human and the robot. Relative to previous energy shaping controllers for assistive exoskeletons, we introduce ground reaction force and torque information into the target behavior definition, reformulate the kinematics so as to avoid explicit matching conditions due to under-actuation, and avoid the need to switch between swing and stance energy shapes. Our controller introduces new states into the target Hamiltonian energy that represent a virtual second leg that is connected to the physical leg using virtual springs. The impulse the human imparts to the physical leg is amplified and applied to the virtual leg, but the ground reaction force acts only on the physical leg. A state transformation allows the proposed control to be available using only encoders, an IMU, and ground reaction force sensors. We prove that this controller is stable and passive when acted on by the ground reaction force and demonstrate the controller's strength amplifying behavior in a simulation. A linear analysis based on small signal assumptions allows us to explain the relationship between our tuning parameters and the frequency domain amplification bandwidth. 

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3. Eye-Track Modeling of Problem-Solving in Virtual Manufacturing Environments

   Zhu, Rui ; Aqlan, Faisal ; Zhao, Richard ; Yang, Hui ( July 2021 , ASEE annual conference proceedings)

   null (Ed.)

   Problem-solving focuses on defining and analyzing problems, then finding viable solutions through an iterative process that requires brainstorming and understanding of what is known and what is unknown in the problem space. With rapid changes of economic landscape in the United States, new types of jobs emerge when new industries are created. Employers report that problem-solving is the most important skill they are looking for in job applicants. However, there are major concerns about the lack of problem-solving skills in engineering students. This lack of problem-solving skills calls for an approach to measure and enhance these skills. In this research, we propose to understand and improve problem-solving skills in engineering education by integrating eye-tracking sensing with virtual reality (VR) manufacturing. First, we simulate a manufacturing system in a VR game environment that we call a VR learning factory. The VR learning factory is built in the Unity game engine with the HTC Vive VR system for navigation and motion tracking. The headset is custom-fitted with Tobii eye-tracking technology, allowing the system to identify the coordinates and objects that a user is looking at, at any given time during the simulation. In the environment, engineering students can see through the headset a virtual manufacturing environment composed of a series of workstations and are able to interact with workpieces in the virtual environment. For example, a student can pick up virtual plastic bricks and assemble them together using the wireless controller in hand. Second, engineering students are asked to design and assemble car toys that satisfy predefined customer requirements while minimizing the total cost of production. Third, data-driven models are developed to analyze eye-movement patterns of engineering students. For instance, problem-solving skills are measured by the extent to which the eye-movement patterns of engineering students are similar to the pattern of a subject matter expert (SME), an ideal person who sets the expert criterion for the car toy assembly process. Benchmark experiments are conducted with a comprehensive measure of performance metrics such as cycle time, the number of station switches, weight, price, and quality of car toys. Experimental results show that eye-tracking modeling is efficient and effective to measure problem-solving skills of engineering students. The proposed VR learning factory was integrated into undergraduate manufacturing courses to enhance student learning and problem-solving skills. 

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4. Inclusion of actuator dynamics in simulations of assisted human movement

   https://doi.org/10.1002/cnm.3334  

   Nguyen, Vinh Q. ; LaPre, Andrew K. ; Price, Mark A. ; Umberger, Brian R. ; Sup, IV, Frank C. ( March 2020 , International Journal for Numerical Methods in Biomedical Engineering)

   Simulation of musculoskeletal systems using dynamic optimization is a powerful approach for studying the biomechanics of human movements and can be applied to human‐robot interactions. The simulation results of human movements augmented by robotic devices may be used to evaluate and optimize the device design and controller. However, simulations are limited by the accuracy of the models which are usually simplified for computation efficiency. Typically, the powered robotic devices are often modeled as massless, ideal torque actuators that is without mass and internal dynamics, which may have significant impacts on the simulation results. This article investigates the effects of including the mass and internal dynamics of the device in simulations of assisted human movement. The device actuator was modeled in various ways with different detail levels. Dynamic optimization was used to find the muscle activations and actuator commands in motion tracking and predictive simulations. The results showed that while the effects of device mass and inertia can be small, the electrical dynamics of the motor can significantly impact the results. This outcome suggests the importance of using an accurate actuator model in simulations of human movement augmented by assistive devices.

   Demonstrating the effects of including mass and internal dynamics of the actuator in simulations of assisted human movement

   A new OpenSim electric motor actuator class to capture the electromechanical dynamics for use in simulation of human movement assisted by powered robotic devices

    

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5. Architecting the Cooperative 3D Printing System

   https://doi.org/10.1115/DETC2020-22711  

   Poudel, Laxmi ; Marques, Lucas Galvan ; Williams, Robert Austin ; Hyden, Zachary ; Guerra, Pablo ; Fowler, Oliver Luke ; Moquin, Stephen Joe ; Sha, Zhenghui ; Zhou, Wenchao ( August 2020 , 40th Computers and Information in Engineering Conference (CIE))

   null (Ed.)

   Cooperative 3D printing (C3DP) is a novel approach to additive manufacturing, where multiple mobile 3D printing robots work together cooperatively to print the desired part. At the core of C3DP lies the chunk-based printing strategy. This strategy splits the desired part into smaller chunks, and then the chunks are assigned and scheduled to be printed by individual printing robots. In our previous work, we presented various hardware and software components of C3DP, such as mobile 3D printers, chunk-based slicing, scheduling, and simulation. In this study, we present a fully integrated and functional C3DP platform with all necessary components, including chunker, slicer, scheduler, printing robots, build floor, and outline how they work in unison from a system-level perspective. To realize C3DP, new developments of both hardware and software are presented, including new chunking approaches, scalable scheduler for multiple robots, SCARA-based printing robots, a mobile platform for transporting printing robots, modular floor tiles, and a charging station for the mobile platform. Finally, we demonstrate the capability of the system using two case studies. In these demonstrations, a CAD model of a part is fed to the chunker, divided into smaller chunks, passed to the scheduler, and assigned and scheduled to be printed by the scheduler with a given number of robots. The slicer generates G-code for each of the chunks and combines G-code into one file for each robot. The simulator then uses the G-code generated by the slicer to generate animations for visualization purposes.

    

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