The United States Science & Engineering Olympiad (USSEO) challenges teams to push the boundaries of their hardware by designing a smart, AI-integrated robotic solution to a real-world issue of their choice.
In this challenge, teams must implement a “Human-in-the-Loop” workflow, using Artificial Intelligence for perception and data analysis, while ensuring human judgment remains central to the robot’s operation. Using existing lab hardware and working within a compact 40 cm × 40 cm × 40 cm footprint, teams will document their engineering journey and present a working prototype.
The USSEO, operated by Luminas Inc., is pleased to announce its partnership with the Robotics Education & Competition Foundation network through this Online Challenge. Luminas Inc is a U.S.based nonprofit organization dedicated to empowering the next generation of scientists, engineers, researchers, and innovators. Through this partnership, USSEO aims to foster technical excellence, creative problem-solving, and advanced scientific inquiry across participating student communities.
To complete this challenge and be eligible for the prizes and awards you need to successfully submit all materials to the challenge.
Objective: Identify a real-world problem and design a solution integrating AI, human judgment, and robotic execution.
Process: Submit a 1-2 page Ideation Proposal defining the targeted problem, impacted audience, and why a Human-in-the-Loop AI solution is necessary. Submit the proposal document via USSEO portal to enter Phase 2.
Elementary&Middle School Division: Open Themes. The participating teams have no restrictions on their project theme.
High School Division: Teams must select and align their project with one of the official designated themes for the 2027 season:
Objective: Construct a physical prototype based on the proposal, integrating custom code and AI models.
Process: Document prototype development, system integration, testing, and iterative improvements in the Engineering Notebook.
The tiered expectations for AI integration scale with each division, from using ready-made AI tools to selecting, validating, and explaining AI systems independently. Human-in-the-Loop is required throughout all divisions: the AI supports a human’s decisions rather than replacing them.
Participants are not required to develop AI from scratch or program AI algorithms.
They use block-based programming environments, educational machine learning platforms (such as Teachable Machine), pre-trained AI models, or AI services, and incorporate the AI’s results into their projects.
Participants integrate AI/ML models with the project’s sensors, software, and robot systems as one cohesive system.
They understand and explain the AI’s inputs, outputs, and role, why it was selected, and how it is used in the project.
Participants select AI technologies or models suited to the project’s purpose and demonstrate an understanding of the relevant data, inference process, performance, and system integration methods. As appropriate, they may train models, use pre-trained models, or use AI APIs and frameworks, and they verify and explain their AI system’s design methodology and performance.
For more information, please refer to our official guidelines.
