@people_and_robots/lively_tk NPM

LivelyTK v0.9.33 (beta)

NOTE: Since LivelyTK is still in beta, the design is subject to change and should not be considered final!

About

LivelyTK Package

The LivelyTK framework provides a highly configurable toolkit for commanding robots in mixed modalities while incorporating liveliness motions. It is adapted from RelaxedIK framework, and compatible with Python and Javascript/Node.

To configure a robot, the easiest method is to use the LivelyStudio interface in the lively_tk_ros repository, which is a wizard for configuring the robot.

Configuring

Configuring of LivelyTK is centered on the Solver class, which you can instantiate in the following ways:

python

from lively_tk import Solver, PositionMatchObjective, OrientationMatchObjective, SmoothnessMacroObjective, CollisionAvoidanceObjective, State, Transform, ScalarRange, BoxShape
solver = Solver(
    urdf='<?xml version="1.0" ?><robot name="panda">...</robot>', # Full urdf as a string
    objectives=[
        PositionMatchObjective(name="EE Position",link="panda_hand",weight=50),
        OrientationMatchObjective(name="EE Rotation",link="panda_hand",weight=25),
        SmoothnessMacroObjective(name="General Smoothness",weight=10),
        CollisionAvoidanceObjective(name="Collision Avoidance",weight=10)
        ...
    ], 
    root_bounds=[
        ScalarRange(value=0.0,delta=0.0),ScalarRange(value=0.0,delta=0.0),ScalarRange(value=0.0,delta=0.0), # Translational
        ScalarRange(value=0.0,delta=0.0),ScalarRange(value=0.0,delta=0.0),ScalarRange(value=0.0,delta=0.0)  # Rotational
    ],
    shapes=[
        BoxShape(name="Table",frame="world",physical=True,x=2,y=1,z=1.2,local_transform=Transform.isometry())
    ], 
    initial_state=State(origin=Transform.identity(),joints={"panda_joint1":0.0,"panda_joint2":0.0,...}), # Optional
    only_core=False, # Only use this flag if you are not using liveliness objectives and want a slight speed-up.
    max_retries=1, # Number of times the solution is attempted (default 1)
    max_iterations=150 # Number of iterations per try (default 150)
)

javascript

import {
    Solver, PositionMatchObjective, OrientationMatchObjective, 
    SmoothnessMacroObjective, CollisionAvoidanceObjective, 
    State, Transform, ScalarRange, BoxShape} from "@people_and_robots/lively_tk";

let solver = new Solver(
    '<?xml version="1.0" ?><robot name="panda">...</robot>', // Full urdf as a string
    [
        {type:'PositionMatch',name:"EE Position",link:"panda_hand",weight:50},
        {type:'OrientationMatch',name:"EE Rotation",link:"panda_hand",weight:25},
        {type:'SmoothnessMacro',name:"General Smoothness",weight:10},
        {type:'CollisionAvoidance',name:"Collision Avoidance",weight:10}
        ...
    ], 
    [
        {value:0.0,delta:0.0},{value:0.0,delta:0.0},{value:0.0,delta:0.0}, // Translational
        {value:0.0,delta:0.0},{value:0.0,delta:0.0},{value:0.0,delta:0.0}  // Rotational
    ],
    [
        {type:'Box',name="Table",frame:"world",physical:True,x:2,y:1,z:1.2,localTransform:{translation:[0,0,0],rotation:[1,0,0,0]}}
    ], 
    {origin:{translation:[0,0,0],rotation:[1,0,0,0]},joints:{panda_joint1:0.0,panda_joint2:0.0,...}}, // Optional
    false, // Only use this flag if you are not using liveliness objectives and want a slight speed-up.
    1, // Number of times the solution is attempted (default 1)
    150 // Number of iterations per try (default 150)
)

Resetting

In both the Javascript and Python interfaces, the Solver class has a reset method that allows the user to reset the state of the solver given some new objective weights and a new robot state. In this case, the robot state only needs to supply the joints and origin field, as shown in the initialization example.

python

solver.reset(state=State(origin=Transform.identity(),joints={"panda_joint1":0.0,"panda_joint2":0.0,...}),weights=[50.0,30.0,20.0,10.0])

javascript

solver.reset(
    {origin:{translation:[0,0,0],rotation:[1,0,0,0]},joints:{panda_joint1:0.0,panda_joint2:0.0,...}}, // New starting state
    [50.0,30.0,20.0,10.0] // New starting weights
)

Solving

The Solver class has a solve method that represents the core functionality of the LivelyTK interface. At a high level, it accepts the following fields:

goals: A list of goal-type objects.
weights: A list of floats, order corresponding to the order of the objectives.
time: (float) The current time. If no liveliness objectives are used, this has no effect.
shapes: A list of shape objects.

The solve method returns a fully-filled State object

Goals

There are a variety of different "goal" types that can be provided. Think of these as settings that you would like to achieve (e.g. a PositionMatch objective accepts a Translation goal).

Translation The translation goal is used by the PositionMatch, PositionMirroring, and OriginPositionMatch objectives.

python

goal = Translation(x:1.0,y:0.0,z:0.5)

javascript

let goal = {Translation:[1.0,0.0,0.5]}

Rotation

The rotation goal is used by the OrientationMatch, OrientationMirroring, and OriginOrientationMatch objectives.

python

goal = Rotation(w:0.707,x:0.0,y:0.0,z:0.707)

javascript

let goal = {Rotation:[0.707,0.0,0.0,0.707]}

Scalar

The scalar goal is used by the JointMatch, JointMirroring, DistanceMatch, JointLiveliness, and RelativeMotionLiveliness objectives.

python

goal = 0.5

javascript

let goal = {Scalar:0.5}

Size

The size goal is used by the PositionLiveliness, OrientationLiveliness, OriginPositionLiveliness, and OriginOrientationLiveliness objectives.

python

goal = Size(x:1.0,y:0.1,z:0.5)

javascript

let goal = {Size:[1.0,0.1,0.5]}

Ellipse

The ellipse goal is used by the PositionBounding objective.

python

goal = Ellipse(
    translation=Translation(x:1.0,y:0.0,z:0.4),
    rotation=Rotation(w:0.707,x:0.0,y:0.0,z:0.707),
    size=Size(x:0.1,y:0.1,z:0.2)
)

javascript

let goal = {Ellipse: {
    pose: {translation: [1.0,0.0,0.4], rotation: [0.707,0.0,0.0,0.707]},
    size: [0.1,0.1,0.2]
}

RotationRange

The rotation range goal is used by the RotationBounding objective.

python

goal = RotationRange(
    rotation=Rotation(w:0.707,x:0.0,y:0.0,z:0.707),
    delta=0.4
)

javascript

let goal = {RotationRange: {
    rotation: [0.707,0.0,0.0,0.707],
    delta:0.4
}

ScalarRange

The scalar range goal is used by the JointBounding objective.

python

goal = ScalarRange(value=0.0,delta=0.4)

javascript

let goal = {ScalarRange: {value:0.0,delta:0.4}

Shapes

There are 4 different Shape classes: Box, Sphere, Capsule, and Cylinder. The name field is entirely for your own usage, and the frame field indicates what robot link the shape is attached to (by default "world"). The physical field indicates whether the shape presents a collision, and should be factored into collision avoidance. Otherwise, the shape is simply tracked in the state if close enough.

Box

python

shape = BoxShape(
    name="camera attachment",
    frame='panda_hand',
    physical=True,
    x=0.5,y=0.5,z=0.2,
    local_transform=Transform.identity())

javascript

let shape = {
    type:'Box',
    name:'camera attachment',
    frame: 'panda_hand',
    physical: true,
    x:0.5,y:0.5,z:0.2,
    local_transform: {translation:[0.0,0.0,0.0],rotation:[1.0,0.0,0.0,0.0]}
    }

Sphere

python

shape = SphereShape(
    name="bouncy ball",
    frame='world',
    physical=True,
    radius=0.1,
    local_transform=Transform.identity())

javascript

let shape = {
    type:'Sphere',
    name:'bouncy ball',
    frame: 'world',
    physical: true,
    radius:0.1,
    local_transform: {translation:[0.0,0.0,0.0],rotation:[1.0,0.0,0.0,0.0]}
    }

Capsule

python

shape = CapsuleShape(
    name="pill",
    frame='world',
    physical=True,
    length=0.2,
    radius=0.1,
    local_transform=Transform.identity())

javascript

let shape = {
    type:'Capsule',
    name:'pill',
    frame: 'world',
    physical: true,
    length:0.2,
    radius:0.1,
    local_transform: {translation:[0.0,0.0,0.0],rotation:[1.0,0.0,0.0,0.0]}
    }

Cylinder

python

shape = CylinderShape(
    name="zone",
    frame='world',
    physical=False,
    length=0.2,
    radius=0.1,
    local_transform=Transform.identity())

javascript

let shape = {
    type:'Cylinder',
    name:'zone',
    frame: 'world',
    physical: false,
    length:0.2,
    radius:0.1,
    local_transform: {translation:[0.0,0.0,0.0],rotation:[1.0,0.0,0.0,0.0]}
    }

State

The State object is the response back after calling solve. It contains the state of the robot in terms of joint and frames, as well as some diagnostic information regarding proximity of various shapes and the center-of-mass of the robot.

Origin

The transform of the root of the robot. This is useful if the root node is movable. Exported as a Transform class (python) or object containing translation and rotation fields (javascript).

Joints

A lookup table of the joint values for each movable joint. Exported as a dictionary (python) or object (javascript).

Frames

A lookup table of the positions/orientations for each link. Exported as a dictionary (python) or object (javascript) of transform objects keyed by the link name.

Proximity

A list of all shapes that are currently tracked and that reach close enough proximity to potentially factor into collision detection. Exported as a ProximityInfo class (python) or object (javascript) with the following attributes:

shape1 (string) The name of the first shape (note, if the robot is initialized with this shape, and it is attached to a robot link, the name is the link it is attached to.)
shape2 (string) The name of the second shape (note, if the robot is initialized with this shape, and it is attached to a robot link, the name is the link it is attached to.)
distance (float/number/None/null) The distance recorded between the two shapes. May possibly be None or null if not tracked, and is zero if the shapes are intersecting.
points (None/set of two points) The closest points on two different shapes that are used determined whether these two shapes are close though to cause a collision based on the distance between the points on these two shapes. points will be None and distance will be 0.0 if two shapes are interesecting and colliding. points will return a set of two points and distance will be greater than 0.0 but smaller than 1.0 if two shapes are close enough(smaller than 1.0) to potentially cause a collision but not yet colliding. Any distance between two points bigger than 1.0 are not considered for collision detection.
physical (bool) True if both shapes are physical, otherwise False.

If the distance between points on two different shapes is 0.0, two shapes are intersecting with each other.
If the distance between points on two different shapes is bigger than 0.0 but smaller than 1.0, two shapes are with in margin with each other.

Center of Mass

A translation (vector) indicating the current center of mass of the robot.

Contributing

Python Instructions

To build, download and cd to this directory. Then run:

# If you just want to install:
python3 setup.py install


# Or if you are developing:
python3 setup.py develop

# If you are developing and need to rebuild:
python3 setup.py clean && python3 setup.py develop

You will need this installed to use the ROS2 LivelyIK Package.

Javascript Instructions

To build, download and cd to this directory. Then run:

# Build the javascript bundle
wasm-pack build --scope people_and_robots --target web -- --features jsbindings

# Pack
wasm-pack pack

# Publish
wasm-pack publish --access=public

@infinitebrahmanuniverse/nolb-_peo @everything-registry/sub-chunk-711 @zalastax/nolb-_peo

3 years ago

3 years ago

3 years ago

3 years ago

3 years ago