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Lab Format & Logistics

Format

The Embodied AI Labs balance concepts, implementation, experimentation, and reflection.

Each repository provides a student-facing README.md for setup and commands and an ASSIGNMENT.md for the required experiments, questions, deliverables, and rubric.

  • Project setup Create a private group repository from the assigned public template and prepare the documented environment.

  • Implementation and checks Complete the assigned components and use the repository’s checks to validate the system incrementally.

  • Experimentation and evaluation Run the required scenarios, collect result artifacts, and compare timing, security, safety, or policy behavior.

  • Discussion and reflection Explain failure cases, safety boundaries, physical outcomes, and the limits of the evaluation.

Deliverables

The canonical deliverables and grading rubric are in the assigned repository’s ASSIGNMENT.md. Typical deliverables include:

  • concise written answers and result tables,
  • completed source code and configuration,
  • required experiment artifacts, and
  • a submission archive generated by the repository’s submission script.

Logistics

The public repositories are templates. Create a private repository for your group, add only your project partners, and do not publish course work in a public repository.

ASU’s Sol supercomputer is the primary platform for compute-intensive project work. Follow the allocation, container, model, and cleanup instructions for your specific project; they are not interchangeable between repositories. Do not run compute-intensive work on a Sol login node.

The course LMS remains authoritative for deadlines, group assignments, and submission. Before uploading, inspect the generated archive and confirm that it contains the current code, answers, and required results.