Skip to main content

Generate trajectories for soft robots from a file

Project description


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


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 .


Minimal Example

import sorotraj

file_to_use = 'traj_setup/setpoint_traj_demo.yaml'

traj = sorotraj.TrajBuilder()
trajectory = traj.get_trajectory()
interp = sorotraj.Interpolator(trajectory)
actuation_fn = interp.get_interp_function(

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:

        # [time, finger1, finger2, n/c, n/c]
            - [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]

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

            - [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 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_traj(conversion_function)
  4. This conversion overwrites the original trajectory. Now you can save it like normal
    • traj.save_traj(file_to_save)
  5. Convert the trajectory definition by passing the conversion function
    • traj.convert_definition(conversion_function)
  6. This conversion overwrites the original trajectory definition and reguilds the trajectory. Now you can save the definition like normal
    • traj.save_definition(file_to_save)

Build an interpolator

interp = sorotraj.Interpolator(trajectory)
  • trajectory: A trajectory object generated by sorotraj.TrajBuilder
actuation_fn, final_time = interp.get_traj_function(
  • 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
cycle_fn = interp.get_cycle_function(
  • 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

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

sorotraj-1.2.4.tar.gz (15.2 kB view hashes)

Uploaded source

Built Distribution

sorotraj-1.2.4-py3-none-any.whl (12.7 kB view hashes)

Uploaded py3

Supported by

AWS AWS Cloud computing Datadog Datadog Monitoring Facebook / Instagram Facebook / Instagram PSF Sponsor Fastly Fastly CDN Google Google Object Storage and Download Analytics Huawei Huawei PSF Sponsor Microsoft Microsoft PSF Sponsor NVIDIA NVIDIA PSF Sponsor Pingdom Pingdom Monitoring Salesforce Salesforce PSF Sponsor Sentry Sentry Error logging StatusPage StatusPage Status page