Interactive Path Planning Algorithm Visualizer
Inspect heuristic graph search wavefronts and continuous sampling-based trees. Compare A*, Dijkstra, Greedy Best-First, and RRT* rewiring on customizable obstacle layouts.
Path Status
Ready
Path Length (Cost)
0.00
Nodes Visited (Closed)
0
Solve Time (CPU)
0.00 ms
Start Node
Goal Node
Wall / Obstacle
Open Set (Frontier)
Visited (Closed Set)
Optimal Solution Path
⚙️ Heuristics & Topology
Distance Heuristic h(n)
Grid Connectivity
Brush Size (Drawing Walls)
1x1
🗺️ Preset Map Environments
📚 Path Planning Theoretical Comparison & ROS 2 Architecture
| Algorithm | Completeness | Optimality | Time Complexity | Space Complexity | Typical Robotics Use Case |
|---|---|---|---|---|---|
| A* Search | Yes (Finite graph) | Yes (Admissible $h(n)$) | $O(b^d)$ worst-case | $O(b^d)$ (Stores all nodes) | ROS 2 Nav2 nav2_smac_planner 2D Grid / Hybrid-A* |
| Dijkstra's Algorithm | Yes | Yes (Shortest path) | $O(|V| \log |V| + |E|)$ | $O(|V|)$ | ROS 2 Nav2 nav2_navfn_planner potential field / costmap |
| Greedy Best-First | No (Can loop/deadlock) | No (Heuristic only) | $O(b^m)$ | $O(b^m)$ | Ultra-fast approximations or games where optimality is non-critical |
| RRT* (Tree Star) | Probabilistically Complete | Asymptotically Optimal | $O(n \log n)$ | $O(n)$ | High-DOF Robotic Arms (MoveIt 2 / OMPL) & Non-Holonomic Vehicles |