GT Cloud Robotics
Georgia Tech VIP Team
About
This course teaches students to build and deploy trustworthy robot autonomy systems at scale. Students will design the infrastructure for composing heterogeneous robotic fleets spanning ground, aerial, and stationary platforms while establishing verifiable safety boundaries between learned policies and trusted controllers. By the end of the course, students will understand how to architect systems where capability scales faster than verification requirements, implement capability-aware protocols that compose vehicles without forcing them into a lowest-common-denominator interface, and deploy learned autonomy in real-world scenarios without certifying the entire stack. Scaling autonomy beyond verification limits: As learned policies and monolithic models replace hand-coded behaviors, traditional whole-stack certification becomes infeasible. The course addresses how to establish contracts between opaque learned components and trusted systems. Heterogeneous fleet composition: Most fleet software is domain-locked or flattens vehicles into generic interfaces that cause silent execution failures. Students learn to build systems that compose diverse platforms without losing platform-specific capabilities. Authority boundaries for learned policies: The course tackles the fundamental question of what contract sits between high-level autonomy (potentially learned, potentially opaque) and low-level controllers, and whether that contract holds when the autonomy layer changes. Cross-platform command validation: Students address the problem of capability-aware command routing—ensuring operators never issue commands vehicles can’t execute, and that validation happens at the protocol level rather than through operator knowledge. Auditable autonomy decisions: The course covers how to log and reconstruct autonomy decisions with enough context to determine post-incident whether failures occurred due to missing invariants or monitor failures.
Majors
Algorithms, Combinatorics and Optimization, Analytics, Computer Science, Cybersecurity, Human-Centered Computing, Human-Computer Interaction, Aerospace Engineering, Analytics, Analytics – Online MS, Computer Engineering, Electrical Engineering, Machine Learning, Mechanical Engineering, Robotics, Applied Physics, Mathematics, Physics, Statistics
How to apply
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