Current projects include developing low-cost autonomous systems for ground and underwater applications. Dr. Mahmoudian and her team are focused on developing a rigorous framework for analyzing, controlling, and navigation of autonomous vehicles for different applications in harsh dynamic environments. The efforts will advance efficient collaborative behavior of autonomous vehicles.
The aim is to develop theoretical, computational, and experimental tools for the long-term operation of a network of autonomous vehicles in complex environments. The key is lowering deployment and operating costs, while also increasing efficiency, endurance and persistence. The application is for air, ground, and sea robots.
The aim is to integrate vehicle robotics, intelligent power electronics and electric power assets to create self-organizing, ad-hoc mobile microgrids to provide power to critical need sites. This system will be capable of regulating power flow at a desired voltage and frequency level meeting load demands. It also can adapt to changes in situation, power demands, or generations.
The aim is to broaden interest and participation in STEM fields through high-interest themes, meaningful contexts, and hands-on activities that engage both the analytical thinking and the integrative design side of the brain. Glider for Problem-solving and Promotion of Interest (GUPPIE) has been developed as a low-cost interdisciplinary pedagogical platform. This research project will study the effectiveness of application-based robotic activities for engaging underrepresented students in STEM.
The specific goals of this project are twofold. The first goal is to design and fabricate a fleet of low-cost highly maneuverable lightweight underwater gliders (UGs). The second goal is to evaluate the capability of the single and multiple developed UGs in littoral zones. The developed UG named ROUGHIE (for Research Oriented Underwater Glider for Hands-On Investigative Engineering) will be smaller in size, lighter in weight, and lower in price than legacy gliders.
This project is focused on developing an autonomous underwater pipeline monitoring navigation system that enables accurate AUV mapping of the pipeline and surrounding area, while dramatically reducing the time and cost of inspections. In collaboration with the Michigan Tech’s Great Lakes Research Center (GLRC), an autonomous motion-control and navigation algorithm will be developed for an AUV – The Ocean Server IVER3 – to track long linear features such as underwater pipelines.
In order to improve the safety and working environment of mining workers, smart detection systems need to be developed and discussed. The dynamic models and databases for all types of mining machines are the first step to establishing a detection system. The aim of this project is to determine the vehicle kinematics and dynamics for the majority of mobile haulage equipment.
Associate Professor of Mechanical Engineering
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