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Generate trajectories for soft robots from a file

Project description

sorotraj

Generate trajectories for soft robots from yaml files (accompanies the Ctrl-P project)

Installation

Install the release version

This package is on pypi, so anyone can install it with pip: pip install sorotraj

Install the most-recent development version

  1. Clone the package from the github repo
  2. Navigate into the main folder
  3. pip install .

Usage

Minimal Example

import sorotraj

file_to_use = 'traj_setup/setpoint_traj_demo'

traj = sorotraj.TrajBuilder()
traj.load_traj_def(file_to_use)
trajectory = traj.get_trajectory()
interp = sorotraj.Interpolator(trajectory)
actuation_fn = interp.get_interp_function(
                num_reps=1,
                speed_factor=2.0,
                invert_direction=False,
                as_array=False)
print(actuation_fn(2.155))

Check out the examples folder for more detailed usage examples

Set Up Trajectories:

Trajectories are made of three parts:

  1. main: used in a looping trajectory
  2. prefix: happens once before the main part
  3. suffix: happens once after the main part

Here's an example of what that might look like defined in a yaml file:

config:
    setpoints:
        # [time, finger1, finger2, n/c, n/c]
        main:
            - [0.0,   10, 12, 14,  16]
            - [1.0,    20, 0, 0,  0]
            - [2.0,   0, 20, 0,  0]
            - [3.0,     0, 0, 20, 0]
            - [4.0,     0, 0, 0, 20]
            - [5.0,    10, 12, 14, 16]

        prefix:
            - [0.000,   0, 0, 0,  0]
            - [1.0,    10, 12, 14,  16]

        suffix:
            - [2.000,   10, 12, 14,  16]
            - [3.0,  0, 0, 0,  0]

There are currently three types of ways to generate the main part of a trajectory:

  1. direct: You enter waypoints directly
    • Define waypoints as a list of lists of the form: [time in sec], [a_1], [a_2], ..., [a_n]
  2. interp: Interpolate between waypoints
    • Define waypoints as a list of lists of the form: [time in sec], [a_1], [a_2], ..., [a_n]
    • Set a few more parameters:
      • interp_type: (string) The type of interpolation to use. right now types include: 'linear', 'cubic', and 'none'
      • subsample_num: (int) The total number of subsamples over the whole trajectory
  3. waveform: Generate waveforms (very basic, still just in-phase waveforms across all channels)
    • Set up the waveform:
      • waveform_type: (string) Types include: square-sampled, square, sin, cos-up, cos-down, triangle, sawtooth-f, and sawtooth-r
      • waveform_freq: (float) Frequency in Hertz
      • waveform_max: (float) A list of the maximum values for the waveform, in the form: [20, 0, 15, 5]
      • waveform_min: (float) A list of the minimum values for the waveform, in the form: [0, 20, 0, 15]
    • Set a few more parameters:
      • subsample_num: (int) The total number of subsamples over the whole trajectory
      • num_cycles: (int) The number of cycles of the waveform
      • channels: (bool) Flags to turn channels on and off. A list of the form: [1,1,0,0]

Convert Trajectories Line-by-Line

Check out the build_convert_trajectories.py example.

  1. Set up a conversion function
    • Inputs: one original trajectory line (list)
    • Outputs: one new trajectory line (list)
  2. Load the trajectory like normal
    • traj.load_traj_def(file_to_use)
  3. Convert the trajectory by passing the conversion function
    • traj.convert(conversion_function)
  4. This conversion overwrites the original trajectory. Now you can save it like normal
    • traj.save_traj(file_to_save)

Use the Interpolator

interp = sorotraj.Interpolator(trajectory)
  • trajectory: A trajectory object generated by sorotraj.TrajBuilder
actuation_fn = interp.get_interp_function(
                num_reps=1,
                speed_factor=1.0,
                invert_direction=False,
                as_list=False)
  • num_reps: (int, default=1) Number of times to repeat the main looping trajectory
    • Must be positive, nonzero
  • speed_factor: (float, default=1.0) A speed multiplier that is applied to the main loop (but not the prefix or suffix)
    • Must be positive, nonzero
  • invert_direction: (bool, default=False) Negate the whole trajectory (useful if actuators have different directionalities)
    • (bool): Negate all channels
    • (list of ints): Choose which channels to negate with a list of channel indices
  • as_list: (bool, default=False) get the interpolation function as a list of 1D functions (one for each channel) rather than a single 2D interpolation
cycle_fn = interp.get_cycle_function(
                num_reps=1,
                speed_factor=1.0,
                invert_direction=False,
                as_list=False)
  • Same inputs as get_interp_function(), but returns a cycle function (returns the current cycle as a function of time)
  • cycle_fn takes these values:
    • -2 = Prefix
    • -1 = Suffix
    • 0-N = Main loop index

Project details


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