The Maze Solver Robot is an autonomous system designed to navigate through complex mazes using sensor-based perception and intelligent pathfinding algorithms. The robot learns the maze layout in real-time and finds the optimal path to the exit.
Raw sensor data was inconsistent and prone to errors affecting navigation accuracy.
Solution: Implemented sensor fusion with averaging filters and calibration routines.
Motors had different speeds causing drift and misalignment in maze navigation.
Solution: Added PID control loops for speed matching and directional correction.
Storing and processing large maze data structures was memory-intensive.
Solution: Optimized data structures and implemented incremental mapping.