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PickAClass · AI Applications (Interdisciplinary) · AI for Robotics & Autonomous Systems

SLAM for Autonomous Navigation

Master Simultaneous Localization and Mapping (SLAM) techniques to enable robots and autonomous vehicles to build maps of unknown environments while simultaneously tracking their own location.

4 courses

Foundations of Vision-Based Autonomous Mobile Robotics

Learn to program and design autonomous robots that navigate, map, and interact with unknown environments using computer vision and modern sensor fusion.

SLAM Foundations: How Robots Map the World and Find Themselves In It

Build a clear, beginner-friendly understanding of Simultaneous Localization and Mapping, how robots build maps while tracking their own location.

Designing a Visual and LiDAR SLAM Stack for a Real Robot

Walk through the practical design of a SLAM stack that combines visual and LiDAR sensors for a real robot, from front-end perception to back-end optimization.

Operating SLAM in the Real World: Deployment, Drift, and Long-Term Reliability

Plan and operate SLAM-driven robots in real environments, with focus on deployment, drift management, map maintenance, and long-term reliability.