def update_callback(pos = None): # Call path planning algorithm. start, goal = gui.get_start_goal() if not (start==None or goal==None): global optimal_path global visited_nodes try: optimal_path, visited_nodes = dijkstra(start, goal, world_obstacles) except Exception, e: print traceback.print_exc()
def update_callback(pos=None): # Call path planning algorithm. start, goal = gui.get_start_goal() if not (start == None or goal == None): global optimal_path global visited_cells try: optimal_path, visited_cells = \ astar_statespace(start, goal, world_obstacles) except Exception, e: print traceback.print_exc()
def update_callback(pos=None): # First apply distance transform to world_obstacles. apply_distance_transform() # Call path planning algorithm. start, goal = gui.get_start_goal() if not (start == None or goal == None): global optimal_path global visited_nodes try: optimal_path, visited_nodes = astar(start, goal, world_obstacles) except Exception, e: print traceback.print_exc()
def update_callback(pos = None): # Call path planning algorithm. start, goal = gui.get_start_goal() if not (start==None or goal==None): global optimal_path global visited_nodes try: optimal_path, visited_nodes = astar(start, goal, world_obstacles) except (Exception, e): print (traceback.print_exc()) # Draw new background. common.draw_background(gui, world_obstacles, visited_nodes, optimal_path)
def update_callback(pos = None): # First apply distance transform to world_obstacles. apply_distance_transform() # Call path planning algorithm. start, goal = gui.get_start_goal() if not (start==None or goal==None): global optimal_path global visited_nodes try: optimal_path, visited_nodes = astar(start, goal, world_obstacles) except Exception, e: print traceback.print_exc()