Simple Python SLAM implementation using A* algorithm and IR frontal proximity sensor of Thymio educational mobile robot.

• 1. Description
• 2. Getting started
  • 2.1 Dependencies
  • 2.2 Installing
  • 2.3 Working conditions
  • 2.4 Executing program
• 3. Version history

Python implementation of Simultaneous Localization And Mapping (SLAM) using IR frontal proximity sensor of a Thymio educational robot. The path towards goal is continuously adjusted according to the newly detected obstacles (cf. YouTube video).

• Tested on macOS Catalina version 10.15.7
• Requires iTerm2 (Build 3.3.9) (or similar Terminal application)
• Python 3.6

pip install -r requirements.txt

⚠️ Do not edit thymio_slam_obstacles_coordinates.txt (this file will be automatically updated as the robot discovers the map on its way towards the goal).

⚠️ Thymio has to be calibrated to turn exactly 90° and to go forward by about 12[cm] (cf. time_turn_left, time_turn_right, time_go_forward, left_adjustment_go_forward, right_adjustment_go_forward).

• Start position: (ys,xs) = (0,0), orient = 'S'.
• The box (0,0) has to be free (start position).
• The box (4,4) has to be free as well (end position, i.e. goal).
• No obstacles should be placed directly on the border of the arena.

python3.6 thymio_slam.py

• 0.1
  • Initial release