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Wireless sensor networks (WSN) are needed for studying Earth’s climate and for real time monitoring of the spread of viruses or pathogens such as those related to Covid-19. The Mapleseed team aims to develop miniaturized robotic vehicles (e.g., microdrones, mini-airplanes, and rovers) capable of carrying various sensors and automatically measuring certain atmospheric parameters and particle/virus concentrations in targeted spaces.
ASML manufactures complex lithography systems critical to the production of microchips, which use high-acceleration linear stages to accomplish incredibly precise tasks. Students on the ASML team will study the dynamics of rolling loops of wires and hoses on these systems, conducting research to develop a simulation of their dynamic behavior, and build a physical test rig to directly measure the resulting motion profiles.
Every year, Constellation Generation moves thousands of nuclear fuel bundles safely in and out of reactor cores in a challenging underwater environment, which is heavily dependent on humans to ensure reliability. Students on this team will aim to eliminate the human element of this critical task, by adapting a robotic tool for underwater nuclear use, reducing the risk of an error.
Honda envisions a future where unmanned aerial vehicles (drones) work in tandem with cars on the road. Students on this team will build on previous path-planning research, developing and testing various use cases for drones to enhance the automotive driving experience, such as increasing the perception range of automobiles by sensing areas, and streaming data back to the autonomous vehicle.
As the presence of robots in our every day life continues to increase, it will be critical to ensure that they can safely and efficiently interact with humans in an uncontrolled environment. Students on the Honda project will develop algorithms to find feasible, collision-free paths for a Clearpath Jackal robot with a Zed2 camera operating in a crowd of pedestrians.
Koppers is one of the leading producers of railroad ties in North America, which is a product that is stored in large outdoor stacks, that makes inventory time-consuming and difficult. The students will develop an autonomous drone-based camera system to determine the amount of a particular product available within inventory stored in an outdoor, multi-acre site.
The MiTek® Automation Technical Development organization is responsible for creating new and improving existing tools that support factory-based component manufacturing for single and multi-family construction. Students on this team will aim to develop a proof-of-concept automated inspection system to ensure that truss components meet all quality inspection criteria.
This project seeks to leap an order of magnitude forward in the domain of software code quality via automated testing. Students on this team will employ Generative AI trained on domain-relevant tests, and continuously educated based on user selection or rejection of generated output, to continuously create system, interface, and unit tests for a complex system.
Accurate and timely assessment of a critically ill patient’s skin is extremely important in preventing pressure injuries from occurring or worsening, and monitoring treatment effectiveness. Students on the Stryker team will design and prototype a device(s) that allow a nurse to access key areas of a patient’s skin with minimal movement of the patient, and minimal effort by the nurse.
Subaru wants to implement advanced AI functionality in their Driver Monitoring System (DMS), leveraging passive IR (infrared) research. Students will develop advanced IR sensor applications for driver monitoring and consumer convenience that will be deployed in our prototype WRX, which is actively being displayed throughout the US at various auto shows, racetracks, and extraneous events.
Walbridge construction company makes jobsite safety a top priority on all their projects, including their two active jobs on U-M’s North Campus. Students on the Walbridge team will develop a Proximity Warning Alert System (PWAS) that detects people, rather than objects, in the blind spots of mobile construction equipment.
