import numpy as np
import traceback
from abr_control.arms import ur5 as arm
# from abr_control.arms import jaco2 as arm
# from abr_control.arms import onelink as arm
from abr_control.controllers import Floating
from abr_control.interfaces import VREP
# initialize our robot config
robot_config = arm.Config(use_cython=True)
# if using the Jaco 2 arm with the hand attached, use the following instead:
# robot_config = arm.Config(use_cython=True, hand_attached=True)
# instantiate the controller
ctrlr = Floating(robot_config, dynamic=True)
# create the VREP interface and connect up
interface = VREP(robot_config, dt=.005)
interface.connect()
# set up arrays for tracking end-effector and target position
ee_track = []
try:
feedback = interface.get_feedback()
start = robot_config.Tx('EE', q=feedback['q'])
# run ctrl.generate once to load all functions
zeros = np.zeros(robot_config.N_JOINTS)
ctrlr.generate(q=zeros, dq=zeros)
mode, which only compensates for gravity. The end-effector position
is recorded and plotted when the script is exited (with ctrl-c).
"""
import numpy as np
import traceback
from abr_control.arms import ur5 as arm
# from abr_control.arms import jaco2 as arm
# from abr_control.arms import onelink as arm
from abr_control.controllers import Floating
from abr_control.interfaces import VREP
# initialize our robot config
robot_config = arm.Config(use_cython=True)
# instantiate the controller
ctrlr = Floating(robot_config)
# create the VREP interface and connect up
interface = VREP(robot_config, dt=.001)
interface.connect()
# set up arrays for tracking end-effector and target position
ee_track = []
try:
feedback = interface.get_feedback()
start = robot_config.Tx('EE', q=feedback['q'])
while 1:
# get joint angle and velocity feedback
feedback = interface.get_feedback()
# calculate the control signal
In this example, the floating controller is applied in the joint space
"""
import numpy as np
import traceback
import glfw
from abr_control.controllers import Floating
from abr_control.arms.mujoco_config import MujocoConfig as arm
from abr_control.interfaces.mujoco import Mujoco
from abr_control.utils import transformations
# initialize our robot config
robot_config = arm('jaco2')
# instantiate the controller
ctrlr = Floating(robot_config, task_space=True, dynamic=True)
# create the Mujoco interface and connect up
interface = Mujoco(robot_config, dt=.001)
interface.connect()
interface.send_target_angles(robot_config.START_ANGLES)
# set up arrays for tracking end-effector and target position
ee_track = []
q_track = []
try:
# get the end-effector's initial position
feedback = interface.get_feedback()
start = robot_config.Tx('EE', q=feedback['q'])
is recorded and plotted when the script is exited (with ctrl-c).
In this example, the floating controller is applied in the joint space
"""
import traceback
import numpy as np
from abr_control.arms import jaco2 as arm
from abr_control.controllers import Floating
from abr_control.interfaces import CoppeliaSim
# initialize our robot config
robot_config = arm.Config()
# instantiate the controller
ctrlr = Floating(robot_config, dynamic=False, task_space=False)
# create the CoppeliaSim interface and connect up
interface = CoppeliaSim(robot_config, dt=0.005)
interface.connect()
# set up arrays for tracking end-effector and target position
ee_track = []
q_track = []
try:
# get the end-effector's initial position
feedback = interface.get_feedback()
start = robot_config.Tx("EE", q=feedback["q"])
print("\nSimulation starting...\n")
"""Uses force control to compensate for gravity. The arm will
hold its position while maintaining compliance. """
import numpy as np
import traceback
import time
import abr_jaco2
from abr_control.controllers import Floating
# initialize our robot config
robot_config = abr_jaco2.Config(
use_cython=True)
ctrlr = Floating(robot_config, dynamic=True, task_space=True)
# run controller once to generate functions / take care of overhead
# outside of the main loop, because force mode auto-exits after 200ms
zeros = np.zeros(robot_config.N_JOINTS)
ctrlr.generate(zeros, zeros)
# create our interface for the jaco2
interface = abr_jaco2.Interface(robot_config)
q_track = []
u_track = []
q_T_track = []
# connect to the jaco
interface.connect()
interface.init_position_mode()
# Move to home position
***NOTE*** that this is a minimal controller and when other controllers are added (OSC, dynamics_adaptation etc) the control loop time will increase. """ import numpy as np import traceback import timeit import abr_jaco2 from abr_control.controllers import Floating # initialize our robot config robot_config = abr_jaco2.Config(use_cython=True, hand_attached=True) ctrlr = Floating(robot_config) # run controller once to generate functions / take care of overhead # outside of the main loop, because force mode auto-exits after 200ms zeros = np.zeros(robot_config.N_JOINTS) ctrlr.generate(zeros, zeros) # create our interface for the jaco2 interface = abr_jaco2.Interface(robot_config) time_track = [] # connect to the jaco interface.connect() interface.init_position_mode() # Move to home position