A ROS-based C++ implementation of the Hybrid A* path planning algorithm for nonholonomic autonomous vehicles, originally developed as part of a master's thesis at KTH. The system takes a binary occupancy grid (from LIDAR) and start/goal poses, then plans a smooth, drivable path using a combination of continuous-space A* with state discretization in heading, constrained (Dubins/Reeds-Shepp) and unconstrained (2D A*) heuristics, and a final gradient-descent smoother that accounts for obstacle clearance, curvature, and smoothness. It also optionally uses a Voronoi diagram to guide the path away from obstacles. The architecture is modular: a central Planner class manages ROS callbacks and orchestrates the search (Algorithm), collision detection (precomputed lookup tables for vehicle footprint), path tracing, and visualization via RViz. The code is well-documented and has been widely cited in autonomous driving research. While it is tightly coupled to ROS 1 (Noetic) and relies on OMPL for Reeds-Shepp heuristics, the core algorithmic components (lookup-based collision checking, Dubins path, gradient smoother) are self-contained and could be extracted for other projects.