Sticky Mitten Avatar API

This repo has been deprecated. See the Magnebot API for the updated API.

A high-level API for TDW's Sticky Mitten Avatar. Try to gather objects and put them at a target goal area as fast as possible!

Generate indoor environments with realistic rigidbody physics and visual rendering that are populated by objects. Some objects are procedurally placed, others are not.
Use the Sticky Mitten Avatar to interact with objects. The Sticky Mitten Avatar is driven entirely by physics in a robotics-esque fashion. Its mittens can attach to objects in the scene. This API adds high-level functionality to the Sticky Mitten Avatar, such as a physics-driven IK system.
The Sticky Mitten Avatar can place objects in containers and then pick up the container to efficiently gather objects in the scene.

Installation

Install TDW. Make sure you are using v1.7.16
Clone this repo.
cd path/to/sticky_mitten_avatar (replace path/to with the actual path).
Install the local sticky_mitten_avatar pip module:

Windows	OS X and Linux
`pip3 install -e . --user`	`pip3 install -e .`

Usage

from sticky_mitten_avatar import StickyMittenAvatarController, Arm

c = StickyMittenAvatarController()
c.init_scene() # Creates an empty room. See API documentation for how to load a furnished scene.
task_status = c.reach_for_target(arm=Arm.left, target={"x": 0.1, "y": 0.6, "z": 0.4})
print(task_status) # TaskStatus.success
c.end()

API

Read this document.

At the start of the simulation, the controller caches static object info per object in the scene and static avatar info.
Each API function returns a TaskStatus indicating whether the action succeeded and if not, why.
After calling each function, the controller updates its FrameData. This data can be used to decide what the avatar's next action will be (pick up an object, navigate around a room, etc.)
Most complex tasks, such as navigation/pathfinding are not implemented in this API because the problem is too unbounded for a simple algorithm. However, given the output data (static object info, static avatar info, and FrameData), an agent equipped with ML data can be trained to do any of these tasks successfully.

API (low-level)

For more information regarding TDW, see the TDW repo.
For more information regarding TDW's low-level Sticky Mitten Avatar API, read this.

How to write your controller

You can write your controller like this:

from sticky_mitten_avatar import StickyMittenAvatarController, Arm

c = StickyMittenAvatarController()
c.init_scene()
task_status = c.reach_for_target(arm=Arm.left, target={"x": 0.1, "y": 0.6, "z": 0.4})
print(task_status) # TaskStatus.success
c.end()

...or this, with your own class:

from sticky_mitten_avatar import StickyMittenAvatarController, Arm

class MyController(StickyMittenAvatarController):
    def my_function(self):
        return self.reach_for_target(arm=Arm.left, target={"x": 0.1, "y": 0.6, "z": 0.4})

if __name__ == "__main__":
    c = MyController()
    c.init_scene()
    print(c.my_function()) # TaskStatus.success
    c.end()

Examples

All example controllers can be found in: controllers/

Controller	Description
`fill_container.py`	Fill a container with objects.
`social_image.py`	Generate the social image for the GitHub preview card.
`initialize_scene.py`	Initialize a floorplan populated with objects.

Tests

Controller	Description
`ik_test.py`	Test the IK chains of the avatar's arms.
`collision_test.py`	Test the avatar's response to collisions.
`turn_test.py`	Test avatar turning.
`composite_object_test.py`	Test if the avatar can grasp a sub-object of a composite object.
`mitten_collision_test.py`	Test mitten collision detection.
`precision_test.py`	Test how the `precision` parameter affects arm articulation.
`proc_gen_spawn_test.py`	Test whether target objects and containers tend to stay in their initial positions.
`target_object_test.py`	Test target objects.

Utility scripts

Utility scripts are located in util/

Script	Description
`composite_object_audio.py`	Get default audio parameters for sub-objects of composite objects.
`occupancy_mapper.py`	Create occupancy maps of each floorplan and layout.
`spawn_mapper.py`	Pre-calculate avatar spawn positions per room, per layout, per scene.
`room_positions.py`	Cache which positions of each occupancy map are in each room.
`occupancy_images.py`	Create an image of each occupancy map per scene per layout.

Troubleshooting and debugging

"I got an error"

Update TDW (pip3 install tdw -U)
Update the TDW build to match the TDW version.
Read this.
If the stacktrace appears to lead to an error not handled in this repo or the tdw repo, create a GitHub issue and we'll address it as soon as possible.
If you see this error, your Internet connection is probably not working:

line 35, in get_major_release
    return v.split(".")[1].strip()
IndexError: list index out of range

"I can't launch in the simulation in a Docker container"

Use the TDW Docker image.
Set launch_build=False in the constructor; otherwise, the controller will try to launch a build on the same machine (outside of the container):

from sticky_mitten_avatar import StickyMittenAvatarController

c = StickyMittenAvatarController(launch_build=False)

"Images are grainy / very dark / obviously glitchy"

Check the player log for Open GL errors.

"I can only initialize a blank white room"

To initialize a realistic indoor environment populated with objects, explicitly set the scene and layout parameters of init_scene().

from sticky_mitten_avatar import StickyMittenAvatarController

c = StickyMittenAvatarController(launch_build=False)
c.init_scene(scene="1a", layout=0)

"The simulation is too slow"

Make sure you're using a GPU.
Make sure the demo parameter in the constructor is False (the default value) and that you don't have an overhead camera. Both will render far more frames than you'll need in an actual simulation; rendering is by far the biggest factor in framerate.
Check the player log for Open GL errors.

"Some actions are slow"

Some actions will take longer to complete than others. For example, move_forward_by(2) will take more time to complete than move_forward_by(1) because the distance is longer.
Sometimes, the avatar's interaction with objects and the environment will cause the action to take a long time. For example, if the arm of the avatar catches on a chair while the avatar is trying to move forward, it will move slower because of the chair's additional mass, friction, etc.

"Sometimes a task fails unexpectedly / The avatar's movements are inaccurate"

This simulation is 100% physics-driven. Every task will sometimes fail. Possible reasons for failure include:

The avatar tried to grasp an object but there was an obstacle in the way.
The avatar tried to move forward but got caught on furniture.
The avatar tried to put an object in a container but the object bounced out.

You will need to develop solutions to handle cases like this. You can use the TaskStatus return values to figure out why a task failed and FrameData to get the current state of the simulation.

"Objects are flying away / The avatar's mitten clipped through a held object / Physics is acting weird in general"

Physics glitches should be very rare but when they do occur, they're usually problems with the Unity physics engine that we can mitigate but not necessarily fix. If you encounter a severe glitch (such as objects falling through the floor), please create a GitHub issue and attach your controller code if possible.

"The simulation behaves differently on different machines / Physics aren't deterministic"

We can't fix this because this is how the Unity physics engine works.

"Objects are dragging on the ground / The avatar loses its grip on objects"

Usually this is because you called grasp_object() without an additional reach_for_target() call. grasp_object() will grasp the object but it won't actually lift it up.

The avatar will lose its grip on objects if it encounters a sufficiently powerful force, such as swinging the object into a wall or dragging it on the floor.

"I need to know what each scene and layout looks like"

Images of each scene+layout combination are here.

Occupancy map images are here.

"I can't navigate through the scene"

There is no built-in navigation system in this API. You'll have to write one yourself.

"The avatar can't go to all positions on the occupancy map"

The occupancy map isn't a navigation map; some "free" positions aren't navigable.

"I have a problem not listed here"

Create a GitHub Issue on this repo. Describe the problem and include steps to reproduce the bug. Please include your controller code if possible.

Changelog

See Changelog.

alters-mit/sticky_mitten_avatar