Welcome to our GitHub organization, we are a team of dedicated students from the Milwaukee School of Engineering (MSOE) embarking on an innovative project: developing an embedded drone system controlled by a Rust-based embedded machine learning system. Our team is committed to pushing the boundaries of autonomous drone technology.
Our project focuses on designing and implementing a completely DIY drone system. The core of our innovation lies in the integration of embedded machine learning, a cutting-edge approach in artificial intelligence, using the Rust programming language known for its safety and performance. This combination ensures a robust, efficient, and reliable system, setting new standards in the field of autonomous drones.
Our group is a blend of students specializing in various disciplines such as computer engineering, software engineering, and electrical engineering. Each member brings a unique set of skills and perspectives, fostering an environment of collaboration and innovation. We are united by our passion for technology and our ambition to contribute meaningfully to the evolving landscape of drone technology.
Innovation in Embedded Systems: Harnessing Rust's capabilities to develop a safe, concurrent, and practical embedded system for drone control. Advancement in Machine Learning: Implementing machine learning algorithms specifically optimized for embedded systems, enhancing the drone's decision-making and responsiveness. Real-World Application: Designing the drone system to be versatile and adaptable for various practical applications, ranging from environmental monitoring to search and rescue operations.
Our project is more than just an academic pursuit; it is a platform for collaboration and open-source contribution. We encourage the involvement of the broader community, welcoming ideas, feedback, and contributions. Through this collaborative spirit, we aim to not only achieve our project goals but also to contribute to the wider open-source community and the field of embedded systems.
Interested parties, including fellow students, researchers, and enthusiasts, are invited to join us in this exciting journey. For more details, collaboration opportunities, or to get involved, please feel free to reach out through one of our emails: [email protected]
