dynamic.md 1.7 KB
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title: Dynamic
Dynamic
Description
This environment is an empty room with moving obstacles. The goal of the agent is to reach the green goal square without colliding with any obstacle. A large penalty is subtracted if the agent collides with an obstacle and the episode finishes. This environment is useful to test Dynamic Obstacle Avoidance for mobile robots with Reinforcement Learning in Partial Observability.
Mission Space
"get to the green goal square"
Action Space
| Num | Name | Action |
|---|---|---|
| 0 | left | Turn left |
| 1 | right | Turn right |
| 2 | forward | Move forward |
| 3 | pickup | Unused |
| 4 | drop | Unused |
| 5 | toggle | Unused |
| 6 | done | Unused |
Observation Encoding
- Each tile is encoded as a 3 dimensional tuple:
(OBJECT_IDX, COLOR_IDX, STATE) OBJECT_TO_IDXandCOLOR_TO_IDXmapping can be found in minigrid/minigrid.pySTATErefers to the door state with 0=open, 1=closed and 2=locked
Rewards
A reward of '1' is given for success, and '0' for failure. A '-1' penalty is subtracted if the agent collides with an obstacle.
Termination
The episode ends if any one of the following conditions is met:
- The agent reaches the goal.
- The agent collides with an obstacle.
- Timeout (see
max_steps).
Registered Configurations
MiniGrid-Dynamic-Obstacles-5x5-v0MiniGrid-Dynamic-Obstacles-Random-5x5-v0MiniGrid-Dynamic-Obstacles-6x6-v0MiniGrid-Dynamic-Obstacles-Random-6x6-v0MiniGrid-Dynamic-Obstacles-8x8-v0MiniGrid-Dynamic-Obstacles-16x16-v0