Angle Path

Angle path planning focuses on finding the shortest path between two points in a space containing obstacles, allowing for movement at any angle, unlike grid-based approaches. Recent research emphasizes efficient algorithms, such as vector-based methods (e.g., R2 and its variants) and wavefront propagation techniques, that prioritize speed and optimality, particularly in complex environments with non-convex obstacles. These advancements improve the performance of pathfinding in robotics, autonomous navigation, and other applications requiring optimal route calculation in cluttered spaces. The development of optimal and bounded-suboptimal multi-agent pathfinding algorithms further extends the applicability of any-angle path planning to more complex scenarios.