lively-tk 0.8.0

A real-time robot motion control framework with built-in liveliness

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.

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.

Once you have a config json file, you can create a Config object from the loaded data using parse_config_data:

import yaml
from datetime import datetime
from lively_tk import parse_config_data, LivelyIK

with open('path/to/config_file.json') as handle:
    config_data = yaml.safe_load(handle)

config = parse_config_data(config_data)

This config can be used to initialize the LivelyTK solver:

solver = LivelyIK(config)

This solver can then be used when providing goals to the solver's solve method:

timestamp = datetime.utcnow().timestamp()
inputs = [
    ObjectiveInput(weight=5.0,vector=[1,2,0]),
    ObjectiveInput(weight=3.0),
    ObjectiveInput(weight=1.0,quaternion=[1,0,0,0])
]
base_position, joint_values, _ = solver.solve(inputs,timestamp,max_retries=2)

The fields for solve are as follows:

1. goals: a list of ObjectiveInput objects.
2. time: (float) The current time. If no liveliness objectives are used, this has no effect.
3. world: [NOT IMPLEMENTED]. Update the current model of the world to handle real-time collision avoidance.
4. max_retries: (int) Number of random restarts to perform when searching for a solution.
5. max_iterations: (int) Number of iterations for each round of search.
6. only_core: (bool) Ignore liveliness objectives and disable the second liveliness optimization. Note: Not advised to switch within runs. Only use this flag if you are not using liveliness objectives and want a slight speed-up.
7. return_frames: (bool) Return the positions and orientations of each joint (structured specified in joint_names in config) as the third output field.

If you need to restart a run, you can execute the reset method of the solver, and provide the starting base position and joint values:

solver.reset([0,0,0],[1,0,1.2,0.4,0.1])