Vaibhav Shende Vaibhav Shende

MicroMouse Goal Navigation

Multiple maze-solving algorithms (Dijkstra, A*, BFS, DFS) optimized for MicroMouse competition with real-time navigation and incremental replanning.

Navigation Software Robotics
GitHub
MicroMouse Goal Navigation

Overview

Maze-solving algorithms optimized for MicroMouse competition with fast computation and memory efficiency.

Dijkstra maze exploration animation A* pathfinding algorithm

Algorithms Implemented

  • Dijkstra: Optimal pathfinding (< 1ms on 16×16 grid)
  • A*: Heuristic-accelerated search
  • BFS: Breadth-first exploration
  • DFS: Depth-first maze exploration
  • Flood Fill: Fast reactive navigation

Features

  • Incremental replanning when new walls discovered
  • Optimized for embedded systems (Arduino/ARM)
  • Competition-ready timing (<3 seconds for solve)
  • Real-time visualization

Technical Details

  • Language: C++
  • Optimization: Memory-efficient, fast computation
  • Target: MicroMouse competition platforms
  • Hardware: Compatible with embedded systems

Getting Started

git clone https://github.com/svaibhav101/MicroMouse-Goal-Navigation.git
mkdir build && cd build
cmake .. && make
# Register with MMS simulator

Competition Results

  • First run: Maze exploration (~40s)
  • Subsequent runs: Optimized path (~10s)
  • Algorithms: Dijkstra/A* for optimal paths
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