Key Engineering Takeaways
- •A* uses a heuristic distance function h(n) to guide the search frontier toward the goal, finding optimal paths 10x-50x faster than Dijkstra.
- •Standard 2D A* assumes circular holonomic robots; Hybrid-A* searches continuous 3D state space [x, y, θ] respecting minimum turning radius.
- •Smac Planner provides collision-aware Reeds-Shepp and Dubins curves for autonomous cars and warehouse tuggers.
Prerequisites
- • Graph search algorithms
- • Costmaps
Dijkstra vs A* vs Hybrid-A* Comparison
Search-based path planning evaluates the total cost $f(n) = g(n) + h(n)$, where $g(n)$ is the exact cost from start to node $n$, and $h(n)$ is the admissible heuristic estimation from node $n$ to the goal.
Tags:#Path Planning#A*#Dijkstra#Smac Planner#Hybrid A*#Nav2