Maze-Solving Autonomous Car (Micromouse)
An STM32-based autonomous micromouse implementing the Flood-Fill algorithm for optimal maze-solving path planning with multiple ToF distance sensors.
Project Overview
This micromouse project showcases advanced autonomous navigation in constrained environments, combining precise sensor integration with sophisticated pathfinding algorithms. Built around the powerful STM32 microcontroller, the system demonstrates real-time decision-making and optimal path planning in unknown maze environments.
The robot utilizes multiple Time-of-Flight (ToF) distance sensors strategically positioned to provide comprehensive wall detection and spatial awareness. The Flood-Fill algorithm implementation enables the micromouse to not only solve mazes but to find the optimal path through iterative exploration and mapping.
The project required careful consideration of real-time constraints, sensor fusion, and motor control precision. The STM32's advanced timer peripherals and interrupt handling capabilities were leveraged to ensure smooth, coordinated movement while maintaining continuous sensor monitoring and path calculation.
Key Features
- • Autonomous maze navigation and solving
- • Flood-Fill algorithm for optimal pathfinding
- • Multiple ToF sensors for precise wall detection
- • Real-time path planning and execution
- • STM32-based control system
- • Optimized movement algorithms
Challenges
- • Implementing Flood-Fill algorithm in real-time constraints
- • Achieving precise wall detection and navigation
- • Coordinating multiple sensors for spatial awareness
- • Optimizing path execution for speed and accuracy
Outcomes
- • Successful maze-solving capability
- • Optimal path finding through Flood-Fill implementation
- • Precise wall detection and navigation
- • Top 10 position in IIT IEEE Micromaze Competition 2024