Trajectories

This file presents the different Trajectories - Command functions available with the Trajectories API

Trajectories - Command functions

This section reference all existing functions to control your robot, which include

• Playing smoothed waypointed trajectories

• Managing saved trajectories

All functions to control the robot are accessible via an instance of the class NiryoRobot

robot = NiryoRobot(<robot_ip_address>)

trajectories = robot.trajectories.get_saved_trajectory_list()
if len(trajectories) > 0:
    robot.trajectories.execute_trajectory_saved(trajectories[0])
...

See examples on Examples Section

List of functions subsections:

Trajectories functions

class Trajectories(client, action_timeout=3600)

get_saved_trajectory(trajectory_name)

Get saved trajectory from robot intern storage Will raise error if position does not exist

Example:

trajectories.get_saved_trajectory("trajectory_01")

Parameters:

trajectory_name (str) – name of the trajectory

Raises:

NiryoRosWrapperException – If trajectory file doesn’t exist

Returns:

list of [j1, j2, j3, j4, j5, j6] in rad

Return type:

list[list[float]]

execute_registered_trajectory(trajectory_name, callback=None)

Execute trajectory from Ned’s memory If a callback function is not passed in parameter, the function will be blocking. Otherwise, the callback will be called when the execution of the function is finished.

Examples:

trajectories.execute_trajectory_saved("trajectory_01")

from threading import Event
trajectory_event = Event()
trajectory_event.clear()

def trajectory_callback(result):
    print(result)
    trajectory_event.set()

trajectories.execute_trajectory_saved("trajectory_01", callback=trajectory_callback)
trajectory_event.wait()

Parameters:

callback (function) – Callback invoked on successful execution.

Return type:

None

execute_trajectory_from_poses(list_poses, dist_smoothing=0.0, callback=None)

Execute trajectory from list of poses If a callback function is not passed in parameter, the function will be blocking. Otherwise, the callback will be called when the execution of the function is finished.

Examples:

trajectory = [[0.3, 0.1, 0.3, 0., 0., 0., 1.],
              [0.3, -0.1, 0.3, 0., 0., 0., 1.],
              [0.3, -0.1, 0.4, 0., 0., 0., 1.],
              [0.3, 0.1, 0.4, 0., 0., 0., 1.]]

trajectories.execute_trajectory_from_poses(trajectory)
trajectories.execute_trajectory_from_poses(trajectory, dist_smoothing=0.02)
trajectories.execute_trajectory_from_poses([[0.3, 0.1, 0.3, 0., 0., 0., 1.], #[x,y,z,qx,qy,qz,qw]
                                     PoseObject(0.3, -0.1, 0.3, 0., 0., 0.),
                                     [0.3, -0.1, 0.4, 0., 0., 0.], #[x,y,z,roll,pitch,yaw]
                                     PoseObject(0.3, 0.1, 0.4, 0., 0., 0.)])

from threading import Event
trajectory_event = Event()
trajectory_event.clear()

def trajectory_callback(result):
    print(result)
    trajectory_event.set()

trajectories.execute_trajectory_from_poses(trajectory, callback=trajectory_callback)
trajectory_event.wait()

Parameters:

• callback (function) – Callback invoked on successful execution.

• list_poses (list[Union[tuple[float], list[float], PoseObject]]) – List of: [x,y,z,qx,qy,qz,qw] or [x,y,z,roll,pitch,yaw] or PoseObject

• dist_smoothing (float) – Distance from waypoints before smoothing trajectory

Return type:

None

save_trajectory(trajectory, trajectory_name, description)

Save trajectory in robot’s memory

Examples:

trajectory = [[0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
              [1.57, 0.0, 0.0, 0.0, -1.57, 0.0],
              [-1.57, 0.0, 0.0, 0.0, -1.57, 0.0]]

trajectories.save_trajectory(trajectory, "trajectory_1", "test description trajectory_1")

Parameters:

• trajectory (list[joints]) – list of joints positions the robot needs to pass by in the trajectory

• trajectory_name (str) – name you give trajectory in the robot’s memory

• description (str) – description you give trajectory in the robot’s memory

Return type:

None

save_last_learned_trajectory(trajectory_name, description)

Save last executed trajectory in robot’s memory

Examples:

trajectories.save_last_learned_trajectory("trajectory_1", "test description trajectory_1")

Parameters:

• trajectory_name (str) – name you give trajectory in the robot’s memory

• description (str) – description you give trajectory in the robot’s memory

Return type:

None

delete_trajectory(trajectory_name)

Delete trajectory from robot’s memory

Example:

if "trajectory_1" in trajectories.get_saved_trajectory_list():
    trajectories.delete_trajectory("trajectory_1")

Return type:

None

clean_trajectory_memory()

Delete all trajectories from robot’s memory

Example:

trajectories.clean_trajectory_memory()

Return type:

None

get_saved_trajectory_list()

Get list of trajectories’ name saved in robot memory

Example:

if "trajectory_1" in trajectories.get_saved_trajectory_list():
    trajectories.delete_trajectory("trajectory_1")

Returns:

list of tuple(trajectory name, trajectory definition)

Return type:

list[tuple(str, str)]

update_trajectory_infos(name, new_name, description='')

Update the trajectory informations: name and description

Example:

trajectories.update_trajectory_infos("trajectory_1", "trajectory_2", callback="change description")

Parameters:

• name (str) – name of the trajectory you want to change infos

• new_name (str) – new name you want to give to the trajectory

• description (str) – new description you want to give to the trajectory

Return type:

None