Map Pathfinding Visualizer

Map Pathfinding Visualizer is an interactive algorithm visualization platform for analyzing how pathfinding methods behave under dynamic obstacles, uncertain map conditions, and changing search constraints.

Key results

• Implemented and visualized core search algorithms including A*, Dijkstra’s, and Breadth-First Search.
• Simulated dynamic obstacles and stochastic sensor noise to study route stability under uncertainty.
• Benchmarked heuristic inflation and replanning frequency, showing roughly 17% higher success under uncertainty with only about 7% runtime overhead.

What I built

• Built an interactive map-based visualization environment for comparing shortest-path and graph-search algorithms in real time.
• Added support for dynamic terrain changes, obstacle updates, and uncertainty-aware path replanning.
• Designed experiments to evaluate how search behavior changes under different heuristic and replanning settings.
• Used the system as a research-oriented tool for understanding safety, efficiency, and robustness tradeoffs in navigation.

Why this matters

Most pathfinding demos show static shortest paths. This system makes algorithm behavior visible under changing conditions, which is closer to how real navigation works in robotics and autonomous systems.