Inspiring the Next Generation: Challenges and Strategies for Onboarding and Retention in an Undergraduate CubeSat Design Team

The University of Toronto Aerospace Team (UTAT) Space Systems Division is a fully student levy-funded, student-led undergraduate design team that develops CubeSats with research-oriented payloads. UTAT’s mission is to provide undergraduate students with unique opportunities to develop engineering design skills outside of the classroom, and therefore has a distinct focus on member growth and education. As an undergraduate student team, UTAT faces a unique set of challenges in onboarding members and maintaining a strong knowledge base on the team. These challenges include onboarding members with limited technical experience, equipping them with satellite design skills, and maintaining high interest levels among volunteer members with limited time to contribute. The team has implemented a wide range of strategies related to onboarding and member development over the past two years. Notable examples include hosting workshops and regular work sessions, and employing practice projects for technical skill development. This paper presents these practices in depth and evaluates their impacts using both quantitative and qualitative metrics of team success including retention rates, team demographic data, and individual perceptions of team dynamics. It also evaluates these practices against scientifically backed models, while evaluating the effectiveness of these models in the student team environment. Lessons learned include the importance of emphasizing a culture of inclusivity and psychological safety as well as utilizing workshops and skill-building modules both in the onboarding phase and throughout the year to generate and maintain interest in the team. The practices presented here are relevant and transferable to similar organizations including student teams, industry projects, and research initiatives

FINCH: A Blueprint for Accessible and Scientifically Valuable Remote Sensing Satellite Missions

Satellite remote sensing missions have grown in popularity over the past fifteen years due to their ability to cover large swaths of land at regular time intervals, making them suitable for monitoring environmental trends such as greenhouse gas emissions and agricultural practices. As environmental monitoring becomes central in global efforts to combat climate change, accessible platforms for contributing to this research are critical. Many remote sensing missions demand high performance of payloads, restricting research and development to organizations with sufficient resources to address these challenges. Atmospheric remote sensing missions, for example, require extremely high spatial and spectral resolutions to generate scientifically useful results. As an undergraduate-led design team, the University of Toronto Aerospace Team’s Space Systems Division has performed an extensive mission selection process to find a feasible and impactful mission focusing on crop residue mapping. This mission profile provides the data needed to improve crop residue retention practices and reduce greenhouse gas emissions from soil, while relaxing performance requirements relative to many active atmospheric sensing missions. This is accompanied by the design of FINCH, a 3U CubeSat with a hyperspectral camera composed of custom and commercial off-the-shelf components. The team’s custom composite payload, the FINCH Eye, strives to advance performance achieved at this form factor by leveraging novel technologies while keeping design feasibility for a student team a priority. Optical and mechanical design decisions and performance are detailed, as well as assembly, integration, and testing considerations. Beyond its design, the FINCH Eye is examined from operational, timeline, and financial perspectives, and a discussion of the supporting firmware, data processing, and attitude control systems is included. Insight is provided into open-source tools that the team has developed to aid in the design process, including a linear error analysis tool for assessing scientific performance, an optical system tradeoff analysis tool, and data processing algorithms. Ultimately, the team presents a comprehensive case study of an accessible and impactful satellite optical payload design process, in hopes of serving as a blueprint for future design teams seeking to contribute to remote sensing research