2023 ASEE Annual Conference & Exposition

Through the synergy of NASA University Leadership Initiative (ULI) Project “Safe Aviation Autonomy with Learning-enabled Components in the Loop: from Formal Assurances to Trusted Recovery Methods” and NSF Excellent in Research (EIR) project “Integrated Sensor-Robot Networks for Real-time Environmental Monitoring and Marine Ecosystem Restoration in the Hampton River”, the authors have successfully developed a research-based course on machine learning and robotics for undergraduate engineering students at Hampton University. This paper presents the goals, challenges, design process, engaging strategies, assessment /outcomes, and lessons learned for the new course. Besides, this paper also presents the integration of IBM AI course and NVIDIA machine learning modules, along with the Couse Extension -two weeks summer undergraduate research experiences on AI/ML and robotics in the Autonomous Systems Laboratory directed by Dr. Marco Pavone at Stanford University. The success in the development of this course is due to the collaboration with Stanford University, which opening Hampton Undergraduate students' eyes to the larger issues in the area of study; due to the support from industry such as IBM and NVDIA, which provide Hampton University free training license for the online course and resources.