def planning(self, sx, sy, gx, gy, ox, oy, robot_radius): obstacle_tree = KDTree(np.vstack((ox, oy)).T) sample_x, sample_y = self.voronoi_sampling(sx, sy, gx, gy, ox, oy) if show_animation: # pragma: no cover plt.plot(sample_x, sample_y, ".b") road_map_info = self.generate_road_map_info( sample_x, sample_y, robot_radius, obstacle_tree) rx, ry = DijkstraSearch(show_animation).search(sx, sy, gx, gy, sample_x, sample_y, road_map_info) return rx, ry
def planning(self, start_x, start_y, goal_x, goal_y, obstacles): nodes = self.generate_graph_node(start_x, start_y, goal_x, goal_y, obstacles) road_map_info = self.generate_road_map_info(nodes, obstacles) if self.do_plot: self.plot_road_map(nodes, road_map_info) plt.pause(1.0) rx, ry = DijkstraSearch(show_animation).search( start_x, start_y, goal_x, goal_y, [node.x for node in nodes], [node.y for node in nodes], road_map_info) return rx, ry