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| from gym_minigrid.minigrid import * | |
| from gym_minigrid.register import register | |
| from operator import add | |
| class DynamicObstaclesEnv(MiniGridEnv): | |
| """ | |
| Single-room square grid environment with moving obstacles | |
| """ | |
| def __init__( | |
| self, | |
| size=8, | |
| agent_start_pos=(1, 1), | |
| agent_start_dir=0, | |
| n_obstacles=4 | |
| ): | |
| self.agent_start_pos = agent_start_pos | |
| self.agent_start_dir = agent_start_dir | |
| # Reduce obstacles if there are too many | |
| if n_obstacles <= size/2 + 1: | |
| self.n_obstacles = int(n_obstacles) | |
| else: | |
| self.n_obstacles = int(size/2) | |
| super().__init__( | |
| grid_size=size, | |
| max_steps=4 * size * size, | |
| # Set this to True for maximum speed | |
| see_through_walls=True, | |
| ) | |
| # Allow only 3 actions permitted: left, right, forward | |
| self.action_space = spaces.Discrete(self.actions.forward + 1) | |
| self.reward_range = (-1, 1) | |
| def _gen_grid(self, width, height): | |
| # Create an empty grid | |
| self.grid = Grid(width, height) | |
| # Generate the surrounding walls | |
| self.grid.wall_rect(0, 0, width, height) | |
| # Place a goal square in the bottom-right corner | |
| self.grid.set(width - 2, height - 2, Goal()) | |
| # Place the agent | |
| if self.agent_start_pos is not None: | |
| self.agent_pos = self.agent_start_pos | |
| self.agent_dir = self.agent_start_dir | |
| else: | |
| self.place_agent() | |
| # Place obstacles | |
| self.obstacles = [] | |
| for i_obst in range(self.n_obstacles): | |
| self.obstacles.append(Ball()) | |
| self.place_obj(self.obstacles[i_obst], max_tries=100) | |
| self.mission = "get to the green goal square" | |
| def step(self, action): | |
| # Invalid action | |
| if action >= self.action_space.n: | |
| action = 0 | |
| # Check if there is an obstacle in front of the agent | |
| front_cell = self.grid.get(*self.front_pos) | |
| not_clear = front_cell and front_cell.type != 'goal' | |
| # Update obstacle positions | |
| for i_obst in range(len(self.obstacles)): | |
| old_pos = self.obstacles[i_obst].cur_pos | |
| top = tuple(map(add, old_pos, (-1, -1))) | |
| try: | |
| self.place_obj(self.obstacles[i_obst], top=top, size=(3,3), max_tries=100) | |
| self.grid.set(*old_pos, None) | |
| except: | |
| pass | |
| # Update the agent's position/direction | |
| obs, reward, done, info = MiniGridEnv.step(self, action) | |
| # If the agent tried to walk over an obstacle or wall | |
| if action == self.actions.forward and not_clear: | |
| reward = -1 | |
| done = True | |
| return obs, reward, done, info | |
| return obs, reward, done, info | |
| class DynamicObstaclesEnv5x5(DynamicObstaclesEnv): | |
| def __init__(self): | |
| super().__init__(size=5, n_obstacles=2) | |
| class DynamicObstaclesRandomEnv5x5(DynamicObstaclesEnv): | |
| def __init__(self): | |
| super().__init__(size=5, agent_start_pos=None, n_obstacles=2) | |
| class DynamicObstaclesEnv6x6(DynamicObstaclesEnv): | |
| def __init__(self): | |
| super().__init__(size=6, n_obstacles=3) | |
| class DynamicObstaclesRandomEnv6x6(DynamicObstaclesEnv): | |
| def __init__(self): | |
| super().__init__(size=6, agent_start_pos=None, n_obstacles=3) | |
| class DynamicObstaclesEnv16x16(DynamicObstaclesEnv): | |
| def __init__(self): | |
| super().__init__(size=16, n_obstacles=8) | |
| register( | |
| id='MiniGrid-Dynamic-Obstacles-5x5-v0', | |
| entry_point='gym_minigrid.envs:DynamicObstaclesEnv5x5' | |
| ) | |
| register( | |
| id='MiniGrid-Dynamic-Obstacles-Random-5x5-v0', | |
| entry_point='gym_minigrid.envs:DynamicObstaclesRandomEnv5x5' | |
| ) | |
| register( | |
| id='MiniGrid-Dynamic-Obstacles-6x6-v0', | |
| entry_point='gym_minigrid.envs:DynamicObstaclesEnv6x6' | |
| ) | |
| register( | |
| id='MiniGrid-Dynamic-Obstacles-Random-6x6-v0', | |
| entry_point='gym_minigrid.envs:DynamicObstaclesRandomEnv6x6' | |
| ) | |
| register( | |
| id='MiniGrid-Dynamic-Obstacles-8x8-v0', | |
| entry_point='gym_minigrid.envs:DynamicObstaclesEnv' | |
| ) | |
| register( | |
| id='MiniGrid-Dynamic-Obstacles-16x16-v0', | |
| entry_point='gym_minigrid.envs:DynamicObstaclesEnv16x16' | |
| ) | |