Summary
- Developed an autonomous robot capable of navigating complex maze environments
- Implemented sensor fusion for accurate position tracking and obstacle detection
- Created efficient pathfinding algorithms for optimal route planning
Autonomous Maze Navigation
Robotics & Embedded Systems
Project Overview
The Autonomous Maze Navigation project was developed as part of the Mechatronics 2 course,
focusing on creating a robot capable of independently navigating through complex maze
environments. The system combines hardware and software components to achieve reliable
autonomous navigation.
The robot utilizes multiple sensors including infrared sensors for wall detection and encoders
for position tracking. The control system was implemented using Arduino, with careful
consideration given to sensor calibration and noise filtering. The navigation algorithm
combines wall-following behavior with path optimization techniques.
One of the main challenges was achieving reliable sensor readings in varying lighting
conditions and maintaining accurate position tracking over extended periods. These challenges
were addressed through sophisticated sensor fusion algorithms and regular calibration
procedures.
Results
The robot successfully demonstrated reliable autonomous navigation through various maze configurations. The implemented sensor fusion approach provided robust position tracking with an accuracy of ±5mm, while the pathfinding algorithms consistently found optimal routes through the maze. The system maintained stable performance across different environmental conditions and achieved a high success rate in maze completion tasks.
Potential Improvements
Future enhancements could include implementing SLAM (Simultaneous Localization and Mapping) for more advanced navigation, adding machine learning capabilities for adaptive path planning, incorporating more sophisticated sensors for improved environmental awareness, and developing a wireless monitoring system for real-time performance analysis.
Core Technologies and Skills
Arduino
C++
Embedded Systems
Sensor Integration
Control Systems
Path Planning
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