Example Concept: Path planning for resource-constrained robots can be optimized by using algorithms that balance computational efficiency and path optimality. For instance, A* algorithm with an admissible heuristic can efficiently find paths in grid-based environments, while D* Lite can dynamically update paths as the environment changes. These algorithms reduce computational load by focusing only on necessary nodes, making them suitable for robots with limited processing power.