The autonomous CO2 sensing rover was designed to navigate office spaces and detect potentially harmful CO2 concentrations, alerting nearby personnel when necessary. The 4-wheeled rover is equipped with a comprehensive sensor suite, including an RPLiDAR, CO2 sensor, infrared sensors, a gyroscope, and an IMU. Utilizing LiDAR-based SLAM, the rover could autonomously navigate an unknown setting, while mapping CO2 levels to create a detailed heat map of concentration across the environment. Key features of this project included a PID controller for precise motion, manual control of the rover via Logitech controller, and algorithms to present the CO2 ppm in an understandable format. 

I focused on developing the autonomous navigation system and translating it into a functional, real-world solution. Using Fusion 360, I designed a simplified CAD model of the robot, optimizing it for performance and sensor placement. The model was then imported into RViz and Gazebo for simulation and testing, allowing me to refine the navigation and obstacle-avoidance strategies in a controlled environment. Leveraging SLAM (Simultaneous Localization and Mapping), I enabled the robot to build real-time maps and autonomously navigate through complex office layouts with precision. This workflow provided a reliable foundation for transitioning the autonomous driving solution from simulation to physical implementation, ensuring that the rover could accurately map environments and navigate while gathering CO2 data autonomously. 

The autonomous CO2 sensing rover successfully demonstrated its ability to navigate autonomously, map indoor spaces in simulation and could monitor CO2 levels with high accuracy. The project achieved a significant milestone by generating a detailed heat map of CO2 concentration across a LiDAR-generated floorplan, providing valuable insights into air quality and potential safety concerns within office environments. The rover’s autonomous navigation system performed reliably in simulation but the team hit a roadblock when translating simulation into reality. Although not fully finished the integration of hardware and software systems in this project showed the rover's potential applications in environmental monitoring and indoor air quality management.