I implemented SLAM (Simultaneous Localization and Mapping) for a 2 dimensional world in this project. We use robot sensor measurements and movement to create a map of an environment from only sensor and motion data gathered by a robot, over time. SLAM tracks the location of a robot in the world in real-time and identify the locations of landmarks such as buildings, trees, rocks, and other world features. This is an active area of research in the fields of robotics and autonomous systems.
- Notebook 1 : robot moving and sensing
- Notebook 2 : Omega and Xi constraints
- Notebook 3 : landmark detection and tracking
- robot_class.py: robot object