Hacked Roomba Autonomous Robot

This project transformed a commercial iRobot Roomba into a fully programmable autonomous robotics platform. By reverse-engineering the Roomba's communication protocol and replacing its control system, the robot gained enhanced capabilities for research and experimentation.

The custom implementation allows for complete control over motor speeds, sensor readings, and navigation algorithms. This opens up possibilities for advanced robotics research, path planning experiments, and integration with external systems.

The electrical modifications centered around integrating an Arduino microcontroller as the main control board. The Roomba's existing motor drivers and power system were preserved and interfaced with the Arduino through custom circuit boards.

Additional sensors were added including ultrasonic rangefinders for distance measurement, IR sensors for cliff detection enhancement, and a 9-DOF IMU for orientation tracking. The power system was modified to provide regulated 5V and 3.3V rails for the new electronics while maintaining the original battery charging capability.

The firmware is written in C++ for Arduino, implementing a state machine for behavior control. Core modules include motor control with PID speed regulation, sensor fusion for obstacle detection, and a simple bug-based navigation algorithm.

The software communicates with a host computer via serial connection, allowing for remote control, telemetry logging, and parameter tuning. The modular architecture makes it easy to test new navigation strategies and sensor configurations.

The hacked Roomba successfully navigates complex indoor environments autonomously, avoiding obstacles and recovering from stuck situations. Battery life remains comparable to the original Roomba (approximately 90 minutes), with the added sensors consuming minimal power.

The platform has been used for testing various navigation algorithms and serves as an educational tool for learning robotics fundamentals. Future improvements could include SLAM integration, camera-based navigation, and ROS compatibility.