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FastSlam Simultaneous Location and Mapping (SLAM) in Python. Developed by me (Bruno) and Lucas Hattori.

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FastSlam Simultaneous Location and Mapping (SLAM) Assignment - Robotics Elements Course

This project is part of the Robotics Elements Course from the department of Mechatronics of the University of São Paulo (USP). It contains two sequential sub-projects: (1) an Extended Kalman Filter (EKF) for state estimation of a controller trycycle and (2) FastSlam, a Simultaneous Location and Mapping (SLAM) implementation built on top of the first assignment. The projects are located at the src directory, and were developed by me (Bruno) and Lucas Hattori.

Features

  • Extended Kalman Filter
  • Particle Filters
  • Simultaneous Location and Mapping (SLAM)

Requirements

  • Python 3
  • Jupyter

Project details

You can check the EKF report and the SLAM report (in Portuguese) for more details on the project.

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FastSlam Simultaneous Location and Mapping (SLAM) in Python. Developed by me (Bruno) and Lucas Hattori.

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