03Plan
Path Planning
planning…
click to move goal
A* over the occupancy grid, with the search itself made visible. The open set expands as a frontier, closed cells fall behind it, and the path resolves once the goal is reached. Drag the heuristic weight to morph the same algorithm between Dijkstra's exhaustive flood and greedy best-first's tunnel vision.
- A* search
- Heuristic weighting
- Obstacle inflation
- Frontier expansion
The heuristic weight is the whole lesson. At 0 the search has no idea where the goal is and floods outward in every direction — that is Dijkstra, and it is optimal but wasteful. At 1 it is A*: still optimal, but the frontier leans toward the goal. Above 1 it stops being optimal and starts guessing, punching a narrow tunnel that can double back badly around obstacles.