Overview

This was a personal project that I undertook after taking Sebastian Thrun's self-driving course on Udacity. My goal was to implement what I learned by building an autonomous mobile robot using the basics of SLAM (simultaneous localization and mapping). The Ultrasonic Mapping Robot uses an Arduino, a servo motor, and an ultrasonic sensor to measure distances while scanning 180 degrees. The measurements and corresponding angles are sent to a computer via Bluetooth and plotted in a GUI controlled by Processing. The GUI is used for path planning and localization based on predicting future measurements. 

System Sequence:

1. Scan and measure

2. Send measurements to my computer

3. Plot measurements

4. Compare predicted anchor points to actual

5. Move the location of the robot on the map to minimize anchor point errors

6. Plan a path to the next measurement location

7. Update location of the robot

8. Generate predicted anchor points

9. Send motor values and time delays to the robot

10. Move the robot to next measurement location with the corresponding motor values

11. Stop motors

12. Repeat steps 1-11

Mapping

path Planning

Localization

Conclusion

This was a fun project that helped me better understand and practice what I learned from Sebastian Thrun's self-driving course on Udacity. Implementing the predicted anchor points to minimize the error between my predicted model and the actual robot made a huge improvement on the accuracy of the map. 

In the future, I would like to use a LIDAR with a depth camera for more accurate measurements and the ability to create a 3D model. I also learned that it would be beneficial to set up an architecture that supports multi-processing, leading to a continuous system sequence.