AI Robotics 200 Introduction to Artificial Intelligence and Robotics

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• Brief Synopsis:
  AI Robotics 200 is a ten-chapter introduction to autonomous robotic systems, moving from foundational control theory through perception, learning, and multi-robot software architecture.
  Part 1 — Foundations of Robot Motion (Ch. 1–5): Starts with the basic control-loop model of a robot (sense → plan → act) and its subsystems, then builds up the math of motion: kinematics and coordinate transforms (with differential-drive robots as the running example), map representations and path planning via A*, reactive/obstacle-avoidance control using state machines, and spatial mapping and localization (including handling sensor drift and landmark correction).
  Part 2 — Learning and Perception (Ch. 6–8): Introduces machine learning and computer vision as applied to robotics, then end-to-end autonomous driving via behavioral cloning (learning control policies directly from sensor-to-action mappings). It closes with multi-robot systems and swarm coordination, using competitive scenarios like soccer and cargo sorting/auction-based task allocation as case studies.
  Part 3 — Robotics Software Architecture (Ch. 9–10): Shifts from algorithms to systems engineering, introducing ROS2 architecture and the publisher/subscriber messaging pattern, teaching students to write ROS2 nodes with subscribers and callbacks.
  Throughout, the text is hands-on — most sections pair concepts with interactive ActiveCode exercises (pathfinding, drift correction, multi-robot auction simulations) rather than pure exposition.

• GitHub repository:

  • https://github.com/CLLiebe/AI_Robotics_200_etextbook

• Link to book preview (e.g. GitHub Pages), if available:

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