MaplessNavigation

Introduction

Reinforcement learning algorithm for mapless navigation, including the simulator based on PyBullet and 3-level reinforcement learning model based on Parl.

Framework

Framework of the project:

MaplessNavigation
|-> env
    |-> maplessNaviEnv.py
|-> robot
    |-> config
        |-> miniBox_parameters.yaml
        |-> scene_parameters.yaml
        |-> task.yaml
    |-> urdf
        |-> miniBox.urdf
    |-> miniBox.py
    |-> register.py
    |-> scene.py
    |-> utils.py
|-> Model.py
|-> Agent.py
|-> Algorithm.py
|-> Train.py
|-> evaluate.py
|-> main.py

env: environment for RL train and test, MaplessNaviEnv in maplessNaviEnv.py is a gym env, you can use it just like the commom gym such as CartPole.
robot: urdf and functions to load and operate robots. YAML in config define several attributes of the robot, scene and task, you can adjust them.

Robot

Robot used in the project is miniBox, which is described in .\robot\urdf\miniBox.urdf.

miniBox is a differentially driven robot. Preview of the model:

Functions regarding to operating robot and create environmental items are implemented in .\robot\utils.py. But you won't call them under normal circumstances.

Scene

We currently provide three scenes in scene.py.

Each scene is a registered class, you can build you own scene. Basic framework of the class to build the scene class is as follows:

@Registers.scenes.register("scene_name")
class SceneX(BaseScene):
    def __init__(self, physicsClientId : int = 0):
        super(SceneX, self).__init__(physicsClientId=physicsClientId)
        
    def construct(self):
        if self.is_built:       
            raise Exception(f"scene_name has been built!")
        self.is_built = True    

        """
            load items to build your own scene
        """

"scene_name" is the registered name you provide, SceneX is the name of the class, you can define it casually as long as it doesn't repeat with other class name

You can use loading function PyBullet provides or the adding function in utils.py to load items in your scene.

Condition to reset the simulator

When distance between miniBox and target point is less than DONE_DISTANCE m or total collision times of the episode reach DONE_COLLISION times, env will reset itself, where DONE_DISTANCE and DONE_COLLISION are defined in task.yaml.