What does LIDAR have to solve:
- Reads environment
- Plots to point
Reading enviornment - Localization
Localization is the ability of a robot to know its position and orientation with sensors
Plotting Path - Path finding
Path planning is the ability of a robot to search feasible and efficient path to the goal. The path has to satisfy some constraints based on the robot’s motion model and obstacle positions, and optimize some objective functions such as time to goal and distance to obstacle.
Takes:
- Destination point
Gives:
- x,y translation vector
LIDAR Tabstack
Resources:
1. https://community.dfrobot.com/makelog-314219.html
DFRobot RPLidar + matplotlib — visualizing live scan data as a polar plot. Directly applicable to where you are right now.
2. https://docs.circuitpython.org/projects/rplidar/en/latest/
Adafruit CircuitPython RPLidar — clean minimal examples for reading scan data into a simple 360-element array. Good reference for structuring your data before feeding it into anything else.
3. https://atsushisakai.github.io/PythonRobotics/
PythonRobotics — runnable Python implementations of every major robotics algorithm: lidar-to-grid mapping, A*, particle filters, SLAM, and more. Use this as a sandbox to understand each piece before integrating them.
4. https://petercorke.github.io/robotics-toolbox-python/mobile_planner.html
Robotics Toolbox for Python — higher-level library built on top of the concepts from PythonRobotics. Good for actually running A* on an occupancy grid with obstacle inflation without writing it from scratch.
5. https://sayantisroboticsblog.blogspot.com/2024/12/diy-lidar-slam-robot-from-scratch.html
DIY LIDAR SLAM from Scratch (2024) — a team that built the full pipeline in pure Python with no ROS. Read this to understand what SLAM is actually doing internally before using a library to do it for you.
6. https://github.com/simondlevy/BreezySLAM
BreezySLAM — the simplest Python SLAM library to get working with your RPLidar. Has an rpslam.py example written specifically for the A1.
7. https://towardsdatascience.com/indoor-robot-localization-with-slam-f8b447bcb865/
Towards Data Science: Indoor SLAM on RPi — practical deployment of BreezySLAM on real hardware with real-time visualization. Read after you have BreezySLAM working on your machine.
8. https://medium.com/@pliam1105/building-a-3d-printed-robot-that-uses-slam-for-autonomous-navigation-cd83473dac7c
Medium: 3D-printed robot with ROS 2 + SLAM (2024) — end-to-end robot build using ROS 2, slam_toolbox, and RPLidar. Only relevant once you're ready to move to ROS.
9. https://robotisim.com/ros-2-slam-beginner-guide-floorplan/
ROS 2 SLAM Beginner Guide — structured walkthrough of the full ROS 2 nav stack: LiDAR → occupancy grid → SLAM Toolbox → Nav2 autonomous navigation. The final destination if you want a production-ready system.