Overview
The Autonomous Firefighting Robot is an engineering project that combines autonomous navigation, sensor based detection, and mechanical actuation. Built as a university assignment done in group of 5, the goal was to create a Raspberry-pi based robot capable of navigating a simulated building, detecting fires represented by colored markers, deploying a reusable foam-cube fire suppressant, and returning to its starting position without hitting obstacles within a three-minute time limit. This project served as a hands-on experience of robotic system integration, sensor-based control, iterative mechanical design, and engineering design process. Project timelines and milestones are managed using Gantt charts.
Fig. 1. Top Diagonal View of the Final Design
Design
The robot was built around a BrickPi platform with dual-motor differential drive, gyroscopic navigation, a motorized color-sensor sweeper, and a reusable claw mechanism for deploying and retrieving a foam-cube fire suppressant. The motorized sensor arm scanned a 180° area in front of the robot while moving. Color measurements were classified using experimentally collected RGB data and clustering to identify fires and obstacles.
Fig. 2. Color sensor on sweeper arm
Challenges & Solutions
Fire Suppression Mechanism
The original fire suppression mechanism design was to mount two foam cubes on a rail and when fire is detected, a stick connected to the motor pushes the cube onto the fire or the rail itself connected to the motor tilts and drops the cube as shown in Figure 4 and 5.
Fig. 4. Initial Design 1
Fig. 5. Initial Design 2
Further tests had shown that the aforementioned implementations were unreliable in a dynamic environment. The mechanism was redesigned as a compact motorized claw that could reliably release and retrieve a single reusable cube as shown in Figure 6 and 7.
Fig. 6. Improved Clamp Design
Fig. 7. Implemented Clamp Design
Navigation Accuracy
Early testing showed inconsistent turning caused by differences in motor performance and uneven mass distribution. A gyroscope-based feedback system was introduced to improve heading control, enabling more consistent straight-line movement and 90° turns.
My Contributions
I served as the team’s project manager and was mainly involved in the designing process, physical testing and design validation. I maintained the project timeline and coordinated milestones using Gantt charts. I created 3D models for the robot subsystems using LeoCAD prior to physical assembly and then tested the movement system, emergency-stop and speaker subsystems, fire-suppression mechanisms, and the final integrated robot. Based on the iterative testing results, I helped redesign the fire suppression mechanism into a compact motorized claw and designed the gyroscope-based feedback system to improve navigation. I also wrote some Python codes for the software integration.
Final Outcome
The final robot could autonomously navigate to the designated room, detect and extinguish two simulated fires, avoid common obstacles, operate an emergency stop and siren, and complete the mission within the required three-minute limit. Gyroscope drift remained the primary limitation and caused inconsistent return-to-base accuracy between runs.
Fig. 8. Final product during trial run
Technologies & Tools: BrickPi · Raspberry Pi · Python · Gyroscope · Color Sensor · Ultrasonic Sensor · Motor · Software Integration · Hardware Testing