Johns Hopkins University 3 credits Robotics and Autonomous Systems
This course explores the principles and practical applications of multi-robot systems (MRS) and swarm intelligence (SI), emphasizing the decentralized and autonomous behaviors that drive robotic collaboration. Students will investigate core algorithms inspired by natural systems—like ant colonies and bird flocks—to understand how distributed decision-making and self-organization emerge in robotics. Through simulations and hands-on projects, students will design, implement, and test algorithms for swarm behaviors such as exploration, foraging, and object transport. Key topics include decentralized control, distributed coordination, and autonomous system development, with a focus on environmental perception, self-awareness, and inter-robot communication. Students will gain experience with tools such as Python, ROS 2, and Gazebo, and will apply their knowledge in a capstone project that synthesizes course concepts. The curriculum also addresses the ethical, legal, and societal considerations of deploying robotic swarms in real-world scenarios, including autonomous vehicles, disaster response, and environmental monitoring. By the end of the course, students will be equipped with both the theoretical foundation and practical skills to analyze, design, and implement multi-robot and swarm intelligence systems. Prerequisite(s): EN.665.645 Artificial Intelligence for Robotics or equivalent proficiency in ROS 2, Python, and Gazebo.
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