A* working ok
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majkellll
parent
af32df4474
commit
15638862d3
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@ -7,4 +7,4 @@ class AgentState:
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def __init__(self, position: Tuple[int, int], orientation: AgentOrientation) -> None:
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self.orientation = orientation
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self.position = position
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self.position = position
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45
bfs.py
45
bfs.py
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@ -7,6 +7,7 @@ from agentOrientation import AgentOrientation
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from queue import Queue, PriorityQueue
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from turnCar import turn_left_orientation, turn_right_orientation
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class Succ:
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state: AgentState
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action: AgentActionType
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@ -19,6 +20,7 @@ class Succ:
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self.cost = cost
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self.predicted_cost = cost
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class SuccList:
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succ_list: list[Succ]
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@ -27,14 +29,17 @@ class SuccList:
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def __lt__(self, other):
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return self.succ_list[-1].predicted_cost < other.succ_list[-1].predicted_cost
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def __gt__(self, other):
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return self.succ_list[-1].predicted_cost > other.succ_list[-1].predicted_cost
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def find_path_to_nearest_can(startState: AgentState, grid: Dict[Tuple[int, int], GridCellType], city: City) -> list[AgentActionType]:
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def find_path_to_nearest_can(startState: AgentState, grid: Dict[Tuple[int, int], GridCellType], city: City) -> list[
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AgentActionType]:
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q: PriorityQueue[SuccList] = PriorityQueue()
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visited: list[AgentState] = []
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startStates: SuccList = SuccList([Succ(startState, AgentActionType.UNKNOWN, 0, _heuristics(startState.position, city))])
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startStates: SuccList = SuccList(
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[Succ(startState, AgentActionType.UNKNOWN, 0, _heuristics(startState.position, city))])
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q.put(startStates)
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while not q.empty():
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currently_checked = q.get()
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@ -45,7 +50,8 @@ def find_path_to_nearest_can(startState: AgentState, grid: Dict[Tuple[int, int],
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for s in successors:
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already_visited = False
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for v in visited:
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if v.position[0] == s.state.position[0] and v.position[1] == s.state.position[1] and s.state.orientation == v.orientation:
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if v.position[0] == s.state.position[0] and v.position[1] == s.state.position[
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1] and s.state.orientation == v.orientation:
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already_visited = True
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break
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if already_visited:
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@ -56,8 +62,7 @@ def find_path_to_nearest_can(startState: AgentState, grid: Dict[Tuple[int, int],
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q.put(SuccList(new_list))
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return []
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def extract_actions(successors: SuccList) -> list[AgentActionType]:
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output: list[AgentActionType] = []
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for s in successors.succ_list:
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@ -65,24 +70,31 @@ def extract_actions(successors: SuccList) -> list[AgentActionType]:
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output.append(s.action)
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return output
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def succ(succ: Succ, grid: Dict[Tuple[int, int], GridCellType], city: City) -> list[Succ]:
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result: list[Succ] = []
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turn_left_cost = 1 + succ.cost
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result.append(Succ(AgentState(succ.state.position, turn_left_orientation(succ.state.orientation)), AgentActionType.TURN_LEFT, turn_left_cost, turn_left_cost + _heuristics(succ.state.position, city)))
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result.append(
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Succ(AgentState(succ.state.position, turn_left_orientation(succ.state.orientation)), AgentActionType.TURN_LEFT,
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turn_left_cost, turn_left_cost + _heuristics(succ.state.position, city)))
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turn_right_cost = 1 + succ.cost
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result.append(Succ(AgentState(succ.state.position, turn_right_orientation(succ.state.orientation)), AgentActionType.TURN_RIGHT, turn_right_cost, turn_right_cost + _heuristics(succ.state.position, city)))
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result.append(Succ(AgentState(succ.state.position, turn_right_orientation(succ.state.orientation)),
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AgentActionType.TURN_RIGHT, turn_right_cost,
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turn_right_cost + _heuristics(succ.state.position, city)))
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state_succ = move_forward_succ(succ, city, grid)
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if state_succ != None:
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result.append(state_succ)
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return result
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def move_forward_succ(succ: Succ, city: City, grid: Dict[Tuple[int, int], GridCellType]) -> Succ:
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position = get_next_cell(succ.state)
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if position == None:
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return None
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cost = get_cost_for_action(AgentActionType.MOVE_FORWARD, grid[position]) + succ.cost
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return Succ(AgentState(position, succ.state.orientation), AgentActionType.MOVE_FORWARD, cost, cost + _heuristics(position, city))
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return Succ(AgentState(position, succ.state.orientation), AgentActionType.MOVE_FORWARD, cost,
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cost + _heuristics(position, city))
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def get_next_cell(state: AgentState) -> Tuple[int, int]:
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@ -102,6 +114,7 @@ def get_next_cell(state: AgentState) -> Tuple[int, int]:
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return None
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return (state.position[0] + 1, state.position[1])
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def is_state_success(state: AgentState, grid: Dict[Tuple[int, int], GridCellType]) -> bool:
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next_cell = get_next_cell(state)
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try:
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@ -109,6 +122,7 @@ def is_state_success(state: AgentState, grid: Dict[Tuple[int, int], GridCellType
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except:
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return False
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def get_cost_for_action(action: AgentActionType, cell_type: GridCellType) -> int:
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if action == AgentActionType.TURN_LEFT or action == AgentActionType.TURN_RIGHT:
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return 1
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@ -120,11 +134,13 @@ def get_cost_for_action(action: AgentActionType, cell_type: GridCellType) -> int
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def is_state_valid(state: AgentState, grid: Dict[Tuple[int, int], GridCellType]) -> bool:
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try:
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return grid[state.position] == GridCellType.STREET_HORIZONTAL or grid[state.position] == GridCellType.STREET_VERTICAL or grid[state.position] == GridCellType.SPEED_BUMP
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try:
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return grid[state.position] == GridCellType.STREET_HORIZONTAL or grid[
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state.position] == GridCellType.STREET_VERTICAL or grid[state.position] == GridCellType.SPEED_BUMP
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except:
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return False
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def _heuristics(position: Tuple[int, int], city: City):
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min_distance: int = 300
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found_nonvisited: bool = False
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@ -137,5 +153,4 @@ def _heuristics(position: Tuple[int, int], city: City):
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min_distance = distance
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if found_nonvisited:
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return min_distance
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return -1
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return -1
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2
city.py
2
city.py
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@ -41,4 +41,4 @@ class City:
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def _render_bumps(self, game_context: GameContext) -> None:
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for bump in self.bumps:
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bump.render(game_context)
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bump.render(game_context)
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4
main.py
4
main.py
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@ -20,10 +20,8 @@ game_context.dust_car_pil = dust_car_pil
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game_context.dust_car_pygame = pygame.image.frombuffer(dust_car_pil.tobytes(), dust_car_pil.size, 'RGB')
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game_context.canvas = canvas
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city = City()
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startup(game_context)
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collect_garbage(game_context, city)
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collect_garbage(game_context)
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exit = False
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@ -10,6 +10,7 @@ import pygame
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from bfs import find_path_to_nearest_can
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from agentState import AgentState
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def collect_garbage(game_context: GameContext) -> None:
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while True:
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start_agent_state = AgentState(game_context.dust_car.position, game_context.dust_car.orientation)
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@ -22,6 +23,7 @@ def collect_garbage(game_context: GameContext) -> None:
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game_context.city.cans_dict[next_position].is_visited = True
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pass
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def move_dust_car(actions: list[AgentActionType], game_context: GameContext) -> None:
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for action in actions:
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street_position = game_context.dust_car.position
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@ -44,7 +46,6 @@ def move_dust_car(actions: list[AgentActionType], game_context: GameContext) ->
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pygame.display.update()
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time.sleep(0.15)
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def calculate_next_position(car: GarbageTruck) -> Tuple[int, int]:
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if car.orientation == AgentOrientation.UP:
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