Full course coming soon

System Architecture for Physical AI and Robotics

7 chapters · 33 lessons

1. 1. Robotics Stack Fundamentals and the Sense-Reason-Act Loop

   4 lessons

   Understand the layered architecture of robotics systems and how continuous feedback loops differ from cloud applications.

2. 2. Sensor Integration and Perception Pipelines

   5 lessons

   Design perception layers that transform noisy physical signals into usable representations for planning and control.

3. 3. Heterogeneous Compute for Robotics Workloads

   5 lessons

   Select and configure compute architectures that balance high-throughput AI inference with low-latency motor control.

4. 4. Planning, Control, and Actuator Precision

   4 lessons

   Translate high-level plans into precise actuator commands while maintaining stability and responsiveness.

5. 5. Safety Monitors and Failure Handling in Physical Systems

   5 lessons

   Implement safety layers that detect hazards and override behavior to prevent damage or injury.

6. 6. Deploying and Managing Robot Fleets

   5 lessons

   Build deployment pipelines with versioning, rollback, observability, and configuration management for distributed robots.

7. 7. Integrating Language Models into Robotics Architectures

   5 lessons

   Connect language models and retrieval systems to robotics stacks for interactive service robots and task interpretation.