def set_camera(camera_name, res):
print "setting", camera_name
camera = CameraController(camera_name)
# camera.resolution = (1280,800)
camera.resolution = res
camera.exposure = 50
camera.gain = 30 #left_hand_camera.gain = CameraController.CONTROL_AUTO
camera.white_balance_red = CameraController.CONTROL_AUTO
camera.white_balance_green = CameraController.CONTROL_AUTO
camera.white_balance_blue = CameraController.CONTROL_AUTO
camera.open()
print "done", camera_name
#!/usr/bin/env python
from baxter_interface import CameraController
if __name__ == '__main__':
camera = CameraController("left_hand_camera")
camera.open()
res = (1280, 800)
camera.resolution = res
camera.exposure = camera.CONTROL_AUTO
camera.fps = 1
camera.gain = camera.CONTROL_AUTO
def main():
"""
Main Script
"""
# Setting up head camera
head_camera = CameraController("left_hand_camera")
head_camera.resolution = (1280, 800)
head_camera.open()
print("setting balance")
happy = False
while not happy:
e = head_camera.exposure
print("exposue value: " + str(e))
e_val = int(input("new exposure value"))
head_camera.exposure = e_val
satisfaction = str(raw_input("satified? y/n"))
happy = 'y' == satisfaction
planner = PathPlanner("right_arm")
listener = tf.TransformListener()
grip = Gripper('right')
grip.calibrate()
rospy.sleep(3)
grip.open()
# creating the table obstacle so that Baxter doesn't hit it
table_size = np.array([.5, 1, 10])
table_pose = PoseStamped()
table_pose.header.frame_id = "base"
thickness = 1
table_pose.pose.position.x = .9
table_pose.pose.position.y = 0.0
table_pose.pose.position.z = -.112 - thickness / 2
table_size = np.array([.5, 1, thickness])
planner.add_box_obstacle(table_size, "table", table_pose)
raw_input("gripper close")
grip.close()
# ###load cup positions found using cup_detection.py ran in virtual environment
# start_pos_xy = np.load(POURING_CUP_PATH)
# goal_pos_xy = np.load(RECEIVING_CUP_PATH)
# start_pos = np.append(start_pos_xy, OBJECT_HEIGHT - GRABBING_OFFSET)
# goal_pos = np.append(start_pos_xy, OBJECT_HEIGHT - GRABBING_OFFSET)
# #### END LOADING CUP POSITIONS
camera_subscriber = rospy.Subscriber("cameras/left_hand_camera/image", Image, get_img)
Kp = 0.1 * np.array([0.3, 2, 1, 1.5, 2, 2, 3]) # Stolen from 106B Students
Kd = 0.01 * np.array([2, 1, 2, 0.5, 0.5, 0.5, 0.5]) # Stolen from 106B Students
Ki = 0.01 * np.array([1, 1, 1, 1, 1, 1, 1]) # Untuned
Kw = np.array([0.9, 0.9, 0.9, 0.9, 0.9, 0.9, 0.9]) # Untuned
cam_pos= [0.188, -0.012, 0.750]
##
## Add the obstacle to the planning scene here
##
# Create a path constraint for the arm
orien_const = OrientationConstraint()
orien_const.link_name = "right_gripper";
orien_const.header.frame_id = "base";
orien_const.orientation.y = -1.0;
orien_const.absolute_x_axis_tolerance = 0.1;
orien_const.absolute_y_axis_tolerance = 0.1;
orien_const.absolute_z_axis_tolerance = 0.1;
orien_const.weight = 1.0;
horizontal = getQuaternion(np.array([0,1,0]), np.pi)
z_rot_pos = getQuaternion(np.array([0,0,1]), np.pi / 2)
orig = quatMult(z_rot_pos, horizontal)
orig = getQuaternion(np.array([0,1,0]), np.pi / 2)
#IN THE VIEW OF THE CAMERA
#CORNER1--------->CORNER2
# | |
# | |
# | |
#CORNER3 ------------|
width = 0.3
length = 0.6
CORNER1 = np.array([0.799, -0.524, -0.03])
CORNER2 = CORNER1 + np.array([-width, 0, 0])
CORNER3 = CORNER1 + np.array([0, length, 0])
#CREATE THE GRID
dir1 = CORNER2 - CORNER1
dir2 = CORNER3 - CORNER1
grid_vals = []
ret_vals = []
for i in range(0, 3):
for j in range(0, 4):
grid = CORNER1 + i * dir1 / 2 + j * dir2 / 3
grid_vals.append(grid)
ret_vals.append(np.array([grid[0], grid[1], OBJECT_HEIGHT]))
i = -1
while not rospy.is_shutdown():
for g in grid_vals:
i += 1
while not rospy.is_shutdown():
try:
goal_1 = PoseStamped()
goal_1.header.frame_id = "base"
#x, y, and z position
goal_1.pose.position.x = g[0]
goal_1.pose.position.y = g[1]
goal_1.pose.position.z = g[2]
y = - g[1] + cam_pos[1]
x = g[0] - cam_pos[0]
q = orig
#Orientation as a quaternion
goal_1.pose.orientation.x = q[1][0]
goal_1.pose.orientation.y = q[1][1]
goal_1.pose.orientation.z = q[1][2]
goal_1.pose.orientation.w = q[0]
plan = planner.plan_to_pose(goal_1, [])
if planner.execute_plan(plan):
# raise Exception("Execution failed")
rospy.sleep(1)
#grip.open()
raw_input("open")
rospy.sleep(1)
# plt.imshow(camera_image)
print("yay: " + str(i))
pos = listener.lookupTransform("/reference/right_gripper", "/reference/base", rospy.Time(0))[0]
print("move succesfully to " + str(pos))
fname = os.path.join(IMAGE_DIR, "calib_{}.jpg".format(i))
skimage.io.imsave(fname, camera_image)
print(e)
print("index: ", i)
else:
break
print(np.array(ret_vals))
# save the positions of the gripper so that the homography matrix can be calculated
np.save(POINTS_DIR, np.array(ret_vals))
print(np.load(POINTS_DIR))
break
