class CozmoWarehouseWorker:
def __init__(self, robot: cozmo.robot.Robot):
self.current_arena_pose = None
self.current_robot_pose = robot.pose
self.robot = robot
# start streaming
robot.camera.image_stream_enabled = True
robot.camera.color_image_enabled = False
robot.camera.enable_auto_exposure()
# Obtain the camera intrinsics matrix
fx, fy = robot.camera.config.focal_length.x_y
cx, cy = robot.camera.config.center.x_y
self.camera_settings = np.array([[fx, 0, cx], [0, fy, cy], [0, 0, 1]],
dtype=np.float)
self.pick_up_pose = Pose(x=4.5, y=13.75, z=0, angle_z=degrees(90))
self.drop_off_pose = Pose(x=21.75, y=13.75, z=0, angle_z=degrees(90))
self.drop_off_directions = [
Pose(x=3, y=4.5, z=0, angle_z=degrees(0)),
Pose(x=21.75, y=4.5, z=0, angle_z=degrees(90)), self.drop_off_pose
]
self.pick_up_directions = [
Pose(x=21.75, y=4.5, z=0, angle_z=degrees(90)),
Pose(x=3, y=4.5, z=0, angle_z=degrees(0)), self.pick_up_pose
]
self.drive_speed = speed_mmps(50)
print("Robot initialized!")
self.grid = CozGrid("map_arena.json")
self.pf = ParticleFilter(self.grid)
print("Robot initialized!")
threading.Thread(target=self.runGUI).start()
def runGUI(self):
self.gui = GUIWindow(self.grid, show_camera=True)
self.gui.show_particles(self.pf.particles)
self.gui.show_mean(0, 0, 0)
self.gui.start()
async def drive_to(self, directions):
print("-" * 20 + "DRIVING" + "-" * 20)
if isinstance(directions, (list, )):
for pose in directions:
await self.__drive_to_pose(pose)
else:
await self.__drive_to_pose(directions)
async def __drive_to_pose(self, pose):
print("We are at ", self.current_arena_pose, " and we are driving to ",
pose)
directions = pose - self.current_arena_pose
print("We will follow these directions: ", directions, "\n\n")
directions.rotation = degrees(pose.rotation)
await self.__execute_directions(directions)
print("Directions followed!", "\n\n")
self.update_current_arena_pose()
def update_current_arena_pose(self):
print("-" * 20 + "UPDATING POSE" + "-" * 20)
coordinate_systems_diff = diff_heading_deg(
self.current_robot_pose.rotation.angle_z.degrees,
self.current_arena_pose.rotation.angle_z.degrees)
arena_initial_pose_mm = rotate_point(
self.current_robot_pose.position.x,
self.current_robot_pose.position.y, coordinate_systems_diff)
arena_final_pose_mm = rotate_point(self.robot.pose.position.x,
self.robot.pose.position.y,
coordinate_systems_diff)
print(
"We think we moved ",
convertPoseFromMmToInches(arena_final_pose_mm -
arena_initial_pose_mm), "\n\n")
self.current_arena_pose = self.current_arena_pose + convertPoseFromMmToInches(
arena_final_pose_mm - arena_initial_pose_mm)
print("Current pose is now ", self.current_arena_pose, "\n\n")
async def pick_up_cube(self, tries=5):
print("-" * 20 + "GETTING CUBE" + "-" * 20)
cube = await self.robot.world.wait_for_observed_light_cube(timeout=30)
print("Found cube: %s" % cube)
picked_up_cube = await self.robot.pickup_object(
cube, num_retries=tries).wait_for_completed().obj
if (picked_up_cube == None):
print("Could not get the cube.")
await self.robot.say_text("Help me!").wait_for_completed()
asyncio.sleep(5)
else:
print("Picked up cube!")
async def set_down_cube(self):
print("-" * 20 + "SETTING DOWN CUBE" + "-" * 20)
await self.robot.set_lift_height(0.0).wait_for_completed()
await self.robot.set_head_angle(degrees(3)).wait_for_completed()
async def __execute_directions(self, directions):
print("Current arena pose is:", self.current_arena_pose, "\n\n")
print("Current robot pose is:", self.robot.pose, "\n\n")
await self.robot.turn_in_place(
angle=degrees(-self.current_arena_pose.rotation.angle_z.degrees)
).wait_for_completed()
print("ROBOT is at AFTER TURNING to be parallel to X: ",
self.robot.pose, "\n\n")
await self.robot.drive_straight(
distance=distance_mm(directions.position.x * self.grid.scale),
speed=self.drive_speed).wait_for_completed()
print("ROBOT is at AFTER DRIVING in the X direction: ",
self.robot.pose, "\n\n")
await self.robot.turn_in_place(angle=degrees(90)).wait_for_completed()
print("ROBOT is at AFTER TURNING to be parallel to Y: ",
self.robot.pose, "\n\n")
await self.robot.drive_straight(
distance=distance_mm(directions.position.y * self.grid.scale),
speed=self.drive_speed).wait_for_completed()
print("ROBOT is at AFTER DRIVING in the Y direction: ",
self.robot.pose, "\n\n")
print("ROBOT is TURNING ",
diff_heading_deg(directions.rotation.angle_z.degrees, 90),
"degrees.", "\n\n")
await self.robot.turn_in_place(angle=degrees(
diff_heading_deg(directions.rotation.angle_z.degrees, 90))
).wait_for_completed()
print("ROBOT is at AFTER FINAL TURN", self.robot.pose, "\n\n")
async def localize(self, turn_angle=20):
print("-" * 20 + "LOCALIZING" + "-" * 20)
# reset our location estimates
conf = False
self.current_arena_pose = Pose(0, 0, 0, angle_z=degrees(0))
self.pf = ParticleFilter(self.grid)
# reset lift and head
await self.robot.set_lift_height(0.0).wait_for_completed()
await self.robot.set_head_angle(degrees(3)).wait_for_completed()
while not conf:
# move a little
self.current_robot_pose = self.robot.pose
await self.robot.turn_in_place(angle=degrees(turn_angle)
).wait_for_completed()
odometry = self.__compute_odometry()
detected_markers, camera_image = await self.__marker_processing()
# update, motion, and measurment with the odometry and marker data
curr_x, curr_y, curr_h, conf = self.pf.update(
odometry, detected_markers)
# update gui
self.gui.show_particles(self.pf.particles)
self.gui.show_mean(curr_x, curr_y, curr_h)
self.gui.show_camera_image(camera_image)
self.gui.updated.set()
self.current_arena_pose = Pose(curr_x,
curr_y,
0,
angle_z=degrees(curr_h))
print("We localized to arena location ", self.current_arena_pose)
def __compute_odometry(self, cvt_inch=True):
'''
Compute the odometry given the current pose of the robot (use robot.pose)
Input:
- curr_pose: a cozmo.robot.Pose representing the robot's current location
- cvt_inch: converts the odometry into grid units
Returns:
- 3-tuple (dx, dy, dh) representing the odometry
'''
last_x, last_y, last_h = self.current_robot_pose.position.x, self.current_robot_pose.position.y, \
self.current_robot_pose.rotation.angle_z.degrees
curr_x, curr_y, curr_h = self.robot.pose.position.x, self.robot.pose.position.y, \
self.robot.pose.rotation.angle_z.degrees
dx, dy = rotate_point(curr_x - last_x, curr_y - last_y, -last_h)
if cvt_inch:
dx, dy = dx / self.grid.scale, dy / self.grid.scale
return (dx, dy, diff_heading_deg(curr_h, last_h))
async def __marker_processing(self, show_diagnostic_image=False):
'''
Obtain the visible markers from the current frame from Cozmo's camera.
Since this is an async function, it must be called using await, for example:
markers, camera_image = await marker_processing(robot, camera_settings, show_diagnostic_image=False)
Input:
- robot: cozmo.robot.Robot object
- camera_settings: 3x3 matrix representing the camera calibration settings
- show_diagnostic_image: if True, shows what the marker detector sees after processing
Returns:
- a list of detected markers, each being a 3-tuple (rx, ry, rh)
(as expected by the particle filter's measurement update)
- a PIL Image of what Cozmo's camera sees with marker annotations
'''
# Wait for the latest image from Cozmo
image_event = await self.robot.world.wait_for(
cozmo.camera.EvtNewRawCameraImage, timeout=30)
# Convert the image to grayscale
image = np.array(image_event.image)
image = color.rgb2gray(image)
# Detect the markers
markers, diag = detect.detect_markers(image,
self.camera_settings,
include_diagnostics=True)
# Measured marker list for the particle filter, scaled by the grid scale
marker_list = [marker['xyh'] for marker in markers]
marker_list = [(x / self.grid.scale, y / self.grid.scale, h)
for x, y, h in marker_list]
# Annotate the camera image with the markers
if not show_diagnostic_image:
annotated_image = image_event.image.resize(
(image.shape[1] * 2, image.shape[0] * 2))
annotator.annotate_markers(annotated_image, markers, scale=2)
else:
diag_image = color.gray2rgb(diag['filtered_image'])
diag_image = Image.fromarray(np.uint8(diag_image * 255)).resize(
(image.shape[1] * 2, image.shape[0] * 2))
annotator.annotate_markers(diag_image, markers, scale=2)
annotated_image = diag_image
return marker_list, annotated_image
cozmo.anim.Triggers.CodeLabUnhappy
).wait_for_completed()
pf = ParticleFilter(grid)
converged = False
else:
# actively look around
# random_degree = np.random.randint(low=85, high=93)
# await robot.turn_in_place(degrees(random_degree),speed=Angle(1080)).wait_for_completed()
robot.drive_wheel_motors(30, 0)
class CozmoThread(threading.Thread):
def __init__(self):
threading.Thread.__init__(self, daemon=False)
def run(self):
cozmo.robot.Robot.drive_off_charger_on_connect = False # Cozmo can stay on his charger
cozmo.run_program(run, use_viewer=False)
if __name__ == '__main__':
# cozmo thread
cozmo_thread = CozmoThread()
cozmo_thread.start()
# init
gui.show_particles(pf.particles)
gui.show_mean(0, 0, 0)
gui.start()
class CozmoWarehouseWorker:
def __init__(self, robot: cozmo.robot.Robot):
self.current_arena_pose = None
self.last_robot_pose = robot.pose
self.robot = robot
# start streaming
await robot.set_head_angle(degrees(3)).wait_for_completed()
robot.camera.image_stream_enabled = True
robot.camera.color_image_enabled = False
robot.camera.enable_auto_exposure()
# Obtain the camera intrinsics matrix
fx, fy = robot.camera.config.focal_length.x_y
cx, cy = robot.camera.config.center.x_y
self.camera_settings = np.array([
[fx, 0, cx],
[ 0, fy, cy],
[ 0, 0, 1]
], dtype=np.float)
self.grid = CozGrid("map_arena.json")
self.pf = ParticleFilter(self.grid)
self.gui = GUIWindow(self.grid, show_camera=True)
self.pick_up_pose = Pose(x=4.5, y=20, 0, angle_z=degrees(90))
self.drop_off_pose = Pose(x=21.75, y=13.75, 0, angle_z=degrees(90))
self.drop_off_directions = [Pose(x=3, y=4.5, 0, angle_z=degrees(0)), Pose(x=21.75, y=4.5, 0, angle_z=degrees(90)), self.drop_off_pose]
self.pick_up_directions = [Pose(x=21.75, y=4.5, 0, angle_z=degrees(90)), Pose(x=3, y=4.5, 0, angle_z=degrees(0)), self.pick_up_pose]
async def drive_to(pose):
print("We are at ", self.current_arena_pose, " and we are driving to ", pose)
directions = pose - self.current_arena_pose
self.__execute_directions(directions)
async def __execute_directions(self, directions):
print("Robot is at: ", self.robot.pose)
await self.robot.turn_in_place(angle=directions.rotation.angle_z).wait_for_completed()
print("ROBOT is at AFTER TURNING to be parallel to X: ", self.robot.pose)
await self.robot.drive_straight(distance=distance_mm(directions.position.x * grid.scale), speed=speed_mmps(80)).wait_for_completed()
print("ROBOT is at AFTER DRIVING in the X direction: ", self.robot.pose)
await self.robot.turn_in_place(angle=degrees(90)).wait_for_completed()
print("ROBOT is at AFTER TURNING to be parallel to Y: ", self.robot.pose)
await self.robot.drive_straight(distance=distance_mm(directions.position.y * grid.scale), speed=speed_mmps(80)).wait_for_completed()
print("ROBOT is at AFTER DRIVING in the Y direction: ", self.robot.pose)
async def localize(self):
# reset our location estimates
conf = False
self.current_arena_pose = Pose(0,0,0,angle_z=degrees(0))
self.pf = ParticleFilter(grid)
# reset lift and head
await self.robot.set_lift_height(0.0).wait_for_completed()
await self.robot.set_head_angle(degrees(3)).wait_for_completed()
while not conf:
# move a little
self.last_robot_pose = self.robot.pose
await self.robot.turn_in_place(angle=degrees(20)).wait_for_completed()
odometry = self.__compute_odometry()
detected_markers, camera_image = await self.__marker_processing()
# update, motion, and measurment with the odometry and marker data
curr_x, curr_y, curr_h, conf = pf.update(odometry, detected_markers)
# update gui
self.gui.show_particles(self.pf.particles)
self.gui.show_mean(curr_x, curr_y, curr_h)
self.gui.show_camera_image(camera_image)
self.gui.updated.set()
self.current_arena_pose = Pose(curr_x , curr_y, 0, angle_z=degrees(curr_h))
def __compute_odometry(self, cvt_inch=True):
'''
Compute the odometry given the current pose of the robot (use robot.pose)
Input:
- curr_pose: a cozmo.robot.Pose representing the robot's current location
- cvt_inch: converts the odometry into grid units
Returns:
- 3-tuple (dx, dy, dh) representing the odometry
'''
last_x, last_y, last_h = self.last_robot_pose.position.x, self.last_robot_pose.position.y, \
self.last_robot_pose.rotation.angle_z.degrees
curr_x, curr_y, curr_h = self.robot.pose.position.x, self.robot.pose.position.y, \
self.robot.pose.rotation.angle_z.degrees
dx, dy = rotate_point(curr_x-last_x, curr_y-last_y, -last_h)
if cvt_inch:
dx, dy = dx / grid.scale, dy / grid.scale
return (dx, dy, diff_heading_deg(curr_h, last_h))
async def __marker_processing(self, show_diagnostic_image=False):
'''
Obtain the visible markers from the current frame from Cozmo's camera.
Since this is an async function, it must be called using await, for example:
markers, camera_image = await marker_processing(robot, camera_settings, show_diagnostic_image=False)
Input:
- robot: cozmo.robot.Robot object
- camera_settings: 3x3 matrix representing the camera calibration settings
- show_diagnostic_image: if True, shows what the marker detector sees after processing
Returns:
- a list of detected markers, each being a 3-tuple (rx, ry, rh)
(as expected by the particle filter's measurement update)
- a PIL Image of what Cozmo's camera sees with marker annotations
'''
# Wait for the latest image from Cozmo
image_event = await self.robot.world.wait_for(cozmo.camera.EvtNewRawCameraImage, timeout=30)
# Convert the image to grayscale
image = np.array(image_event.image)
image = color.rgb2gray(image)
# Detect the markers
markers, diag = detect.detect_markers(image, self.camera_settings, include_diagnostics=True)
# Measured marker list for the particle filter, scaled by the grid scale
marker_list = [marker['xyh'] for marker in markers]
marker_list = [(x/self.grid.scale, y/self.grid.scale, h) for x,y,h in marker_list]
# Annotate the camera image with the markers
if not show_diagnostic_image:
annotated_image = image_event.image.resize((image.shape[1] * 2, image.shape[0] * 2))
annotator.annotate_markers(annotated_image, markers, scale=2)
else:
diag_image = color.gray2rgb(diag['filtered_image'])
diag_image = Image.fromarray(np.uint8(diag_image * 255)).resize((image.shape[1] * 2, image.shape[0] * 2))
annotator.annotate_markers(diag_image, markers, scale=2)
annotated_image = diag_image
return marker_list, annotated_image
class CozmoWarehouseWorker:
def __init__(self, robot: cozmo.robot.Robot):
self.current_arena_pose = None
self.last_robot_pose = robot.pose
self.robot = robot
# start streaming
await robot.set_head_angle(degrees(3)).wait_for_completed()
robot.camera.image_stream_enabled = True
robot.camera.color_image_enabled = False
robot.camera.enable_auto_exposure()
# Obtain the camera intrinsics matrix
fx, fy = robot.camera.config.focal_length.x_y
cx, cy = robot.camera.config.center.x_y
self.camera_settings = np.array([
[fx, 0, cx],
[ 0, fy, cy],
[ 0, 0, 1]
], dtype=np.float)
self.grid = CozGrid("map_arena.json")
self.pf = ParticleFilter(self.grid)
self.gui = GUIWindow(self.grid, show_camera=True)
self.pick_up_pose = Pose(x=4.5, y=20, 0, angle_z=degrees(90))
self.drop_off_pose = Pose(x=21.75, y=13.75, 0, angle_z=degrees(90))
self.drop_off_directions = [Pose(x=3, y=4.5, 0, angle_z=degrees(0)), Pose(x=21.75, y=4.5, 0, angle_z=degrees(90)), self.drop_off_pose]
self.pick_up_directions = [Pose(x=21.75, y=4.5, 0, angle_z=degrees(90)), Pose(x=3, y=4.5, 0, angle_z=degrees(0)), self.pick_up_pose]
async def drive_to(pose):
print("-" * 20)
print("We are at ", self.current_arena_pose, " and we are driving to ", pose)
directions = pose - self.current_arena_pose
print("We will follow these directions: ", directions)
await self.__execute_directions(directions)
print("Directions followed!")
print("-" * 20)
def update_current_arena_pose(self):
arena_starting_pose = rotate_point(self.last_robot_pose, diff_heading_deg(self.last_robot_pose.rotation.degrees, self.cu)
self.current_arena_pose = self.current_arena_pose + convertPoseFromMmToInches(rotate_point(self.robot.pose, - last_robot_pose)
async def __execute_directions(self, directions):
print("Robot is at: ", self.robot.pose)
await self.robot.turn_in_place(angle=directions.rotation.angle_z).wait_for_completed()
print("ROBOT is at AFTER TURNING to be parallel to X: ", self.robot.pose)
await self.robot.drive_straight(distance=distance_mm(directions.position.x * grid.scale), speed=speed_mmps(80)).wait_for_completed()
print("ROBOT is at AFTER DRIVING in the X direction: ", self.robot.pose)
await self.robot.turn_in_place(angle=degrees(90)).wait_for_completed()
print("ROBOT is at AFTER TURNING to be parallel to Y: ", self.robot.pose)
await self.robot.drive_straight(distance=distance_mm(directions.position.y * grid.scale), speed=speed_mmps(80)).wait_for_completed()
print("ROBOT is at AFTER DRIVING in the Y direction: ", self.robot.pose)
async def localize(self):
# reset our location estimates
conf = False
self.current_arena_pose = Pose(0,0,0,angle_z=degrees(0))
self.pf = ParticleFilter(grid)
# reset lift and head
await self.robot.set_lift_height(0.0).wait_for_completed()
await self.robot.set_head_angle(degrees(3)).wait_for_completed()
while not conf:
# move a little
self.last_robot_pose = self.robot.pose
await self.robot.turn_in_place(angle=degrees(20)).wait_for_completed()
odometry = self.__compute_odometry()
detected_markers, camera_image = await self.__marker_processing()
# update, motion, and measurment with the odometry and marker data
curr_x, curr_y, curr_h, conf = pf.update(odometry, detected_markers)
# update gui
self.gui.show_particles(self.pf.particles)
self.gui.show_mean(curr_x, curr_y, curr_h)
self.gui.show_camera_image(camera_image)
self.gui.updated.set()
self.current_arena_pose = Pose(curr_x , curr_y, 0, angle_z=degrees(curr_h))
def __compute_odometry(self, cvt_inch=True):
'''
Compute the odometry given the current pose of the robot (use robot.pose)
Input:
- curr_pose: a cozmo.robot.Pose representing the robot's current location
- cvt_inch: converts the odometry into grid units
Returns:
- 3-tuple (dx, dy, dh) representing the odometry
'''
last_x, last_y, last_h = self.last_robot_pose.position.x, self.last_robot_pose.position.y, \
self.last_robot_pose.rotation.angle_z.degrees
curr_x, curr_y, curr_h = self.robot.pose.position.x, self.robot.pose.position.y, \
self.robot.pose.rotation.angle_z.degrees
dx, dy = rotate_point(curr_x-last_x, curr_y-last_y, -last_h)
if cvt_inch:
dx, dy = dx / grid.scale, dy / grid.scale
return (dx, dy, diff_heading_deg(curr_h, last_h))
async def __marker_processing(self, show_diagnostic_image=False):
'''
Obtain the visible markers from the current frame from Cozmo's camera.
Since this is an async function, it must be called using await, for example:
markers, camera_image = await marker_processing(robot, camera_settings, show_diagnostic_image=False)
Input:
- robot: cozmo.robot.Robot object
- camera_settings: 3x3 matrix representing the camera calibration settings
- show_diagnostic_image: if True, shows what the marker detector sees after processing
Returns:
- a list of detected markers, each being a 3-tuple (rx, ry, rh)
(as expected by the particle filter's measurement update)
- a PIL Image of what Cozmo's camera sees with marker annotations
'''
# Wait for the latest image from Cozmo
image_event = await self.robot.world.wait_for(cozmo.camera.EvtNewRawCameraImage, timeout=30)
# Convert the image to grayscale
image = np.array(image_event.image)
image = color.rgb2gray(image)
# Detect the markers
markers, diag = detect.detect_markers(image, self.camera_settings, include_diagnostics=True)
# Measured marker list for the particle filter, scaled by the grid scale
marker_list = [marker['xyh'] for marker in markers]
marker_list = [(x/self.grid.scale, y/self.grid.scale, h) for x,y,h in marker_list]
# Annotate the camera image with the markers
if not show_diagnostic_image:
annotated_image = image_event.image.resize((image.shape[1] * 2, image.shape[0] * 2))
annotator.annotate_markers(annotated_image, markers, scale=2)
else:
diag_image = color.gray2rgb(diag['filtered_image'])
diag_image = Image.fromarray(np.uint8(diag_image * 255)).resize((image.shape[1] * 2, image.shape[0] * 2))
annotator.annotate_markers(diag_image, markers, scale=2)
annotated_image = diag_image
return marker_list, annotated_image
async def run(robot: cozmo.robot.Robot):
cosimo = CozmoWarehouseWorker()
cosimo.localize()
cosimo.drive_to(cosimo.pick_up_pose)
directions = goal_pose - last_pose
current_pose = last_pose
last_robot_pose = robot.pose
print("SETTING LAST ROBOT POSE TO: ", last_robot_pose)
print("SO WE GOING TO FOLLOW THIS TO PICKUP ZONE:", directions)
await execute_directions(robot, directions)
await robot.turn_in_place(angle=degrees(45)).wait_for_completed()
print("LAST ROBOT POSE IS: ", last_robot_pose)
print("CURRENT POSE IS:", robot.pose)
print("WE THINK WE MOVED THIS MUCH TO GO TO PICKUP ZONE: ", convertPoseToInches(robot.pose - last_robot_pose))
last_robot_pose = robot.pose
print("COZMO THINKS IT IS AT AFTER DRIVING TO PICKUPZONE: ", current_pose)
# await robot.say_text('Ready for pick up!').wait_for_completed()
while True:
cube = await robot.world.wait_for_observed_light_cube(timeout=30)
print("Found cube: %s" % cube)
await robot.pickup_object(cube, num_retries=5).wait_for_completed()
current_pose = current_pose + convertPoseToInches(robot.pose - last_robot_pose)
print("WE THINK WE MOVED THIS MUCH TO PICK UP CUBE: ", convertPoseToInches(robot.pose - last_robot_pose))
last_robot_pose = robot.pose
#cosimo.update_pose()
print("COZMO THINKS IT IS AT AFTER PICKING UP CUBE: ", current_pose)
#await look_around_until_converge(robot)
# intialize an explorer after localized
#cosimo = CozmoExplorer(robot, x_0=last_pose.position.x, y_0=last_pose.position.y, theta_0=last_pose.rotation.angle_z.radians)
# move robot to pickup zone once localized
#print("COZMO CONVERTED THAT TO A START AT:", cosimo.last_arena_pose)
#current_pose = last_pose
# rrt to drop zone and drop off cube
for destination in drop_off_directions:
directions = convertInchesToPose(destination) - current_pose
await execute_directions(robot,directions)
current_pose = current_pose + convertPoseToInches(robot.pose - last_robot_pose)
print("WE THINK WE MOVED THIS MUCH TO FOLLOW DIRECTIONS: ", convertPoseToInches(robot.pose - last_robot_pose))
last_robot_pose = robot.pose
print("COZMO THINKS IT IS AT AFTER FOLLOWING DIRECTIONS: ", current_pose)
#await cosimo.go_to_goal(goal_node=dropoff_node)
await robot.set_lift_height(0.0).wait_for_completed()
# rrt to just in front of pick up zone
# await cosimo.go_to_goal(goal_node=pickup_node)
class CozmoThread(threading.Thread):
def __init__(self):
threading.Thread.__init__(self, daemon=False)
def run(self):
cozmo.robot.Robot.drive_off_charger_on_connect = False # Cozmo can stay on his charger
cozmo.run_program(run, use_viewer=False)
if __name__ == '__main__':
# cozmo thread
cozmo_thread = CozmoThread()
cozmo_thread.start()
# init
gui.show_particles(pf.particles)
gui.show_mean(0, 0, 0)
gui.start()
class CozmoWarehouseWorker:
def __init__(self, robot: cozmo.robot.Robot):
self.current_arena_pose = None
self.current_robot_pose = robot.pose
self.robot = robot
# start streaming
robot.camera.image_stream_enabled = True
robot.camera.color_image_enabled = False
robot.camera.enable_auto_exposure()
# Obtain the camera intrinsics matrix
fx, fy = robot.camera.config.focal_length.x_y
cx, cy = robot.camera.config.center.x_y
self.camera_settings = np.array([
[fx, 0, cx],
[ 0, fy, cy],
[ 0, 0, 1]
], dtype=np.float)
self.current_drop_off_pose_idx = 0
self.pick_up_pose = Pose(x=4.5, y=11, z=0, angle_z=degrees(90))
self.drop_off_poses = [Pose(x=22, y=11, z=0, angle_z=degrees(90)), Pose(x=20, y=11, z=0, angle_z=degrees(90)), Pose(x=18, y=11, z=0, angle_z=degrees(90))]
self.drop_off_directions = [Pose(x=5, y=6, z=0, angle_z=degrees(0)), Pose(x=22, y=6, z=0, angle_z=degrees(90)), self.drop_off_poses[0]]
self.pick_up_directions = [Pose(x=21.75, y=4.5, z=0, angle_z=degrees(0)), Pose(x=5, y=4.5, z=0, angle_z=degrees(90)), self.pick_up_pose]
self.drive_speed = speed_mmps(100)
self.grid = CozGrid("map_arena.json")
self.pf = ParticleFilter(self.grid)
threading.Thread(target=self.runGUI).start()
self.pose_offset = None
def runGUI(self):
self.gui = GUIWindow(self.grid, show_camera=True)
self.gui.show_particles(self.pf.particles)
self.gui.show_mean(0, 0, 0)
self.gui.start()
async def drive_to(self, directions):
print_debug_header("DRIVING")
if isinstance(directions, (list,)):
for pose in directions:
await self.__drive_to_pose(pose)
else:
await self.__drive_to_pose(directions)
async def __drive_to_pose(self, pose):
translation = (pose - self.current_arena_pose).position
directions = Pose(x=translation.x, y=translation.y, z=0, angle_z=pose.rotation.angle_z)
await self.__execute_directions(directions)
self.update_current_arena_pose()
async def __execute_directions(self, directions):
print("Current arena pose is:", self.current_arena_pose, "\n\n")
#print("Current robot pose is:", self.robot.pose, "\n\n")
print("We will follow these directions: ", directions, "\n\n")
initial_position = self.robot.pose.position
await self.robot.turn_in_place(angle=degrees(-self.current_arena_pose.rotation.angle_z.degrees)).wait_for_completed()
#print("ROBOT is at AFTER TURNING to be parallel to X: ", self.robot.pose, "\n\n")
#self.update_current_arena_pose()
await self.robot.drive_straight(distance=distance_mm(directions.position.x * self.grid.scale), speed=self.drive_speed).wait_for_completed()
#print("ROBOT is at AFTER DRIVING in the X direction: ", self.robot.pose, "\n\n")
#self.update_current_arena_pose()
await self.robot.turn_in_place(angle=degrees(90)).wait_for_completed()
#self.update_current_arena_pose()
#print("ROBOT is at AFTER TURNING to be parallel to Y: ", self.robot.pose, "\n\n")
print("TOTAL MOVEMENT IN X: ", math.sqrt((self.robot.pose.position.x - initial_position.x) ** 2 + (self.robot.pose.position.y - initial_position.y) ** 2) / 25.0, "\n")
initial_position = self.robot.pose.position
await self.robot.drive_straight(distance=distance_mm(directions.position.y * (self.grid.scale)), speed=self.drive_speed).wait_for_completed()
#self.update_current_arena_pose()
#print("ROBOT is at AFTER DRIVING in the Y direction: ", self.robot.pose, "\n\n")
#print("ROBOT is TURNING ", diff_heading_deg(directions.rotation.angle_z.degrees, 90), "degrees.", "\n\n")
await self.robot.turn_in_place(angle=degrees(diff_heading_deg(directions.rotation.angle_z.degrees, 90))).wait_for_completed()
#print("ROBOT is at AFTER FINAL TURN", self.robot.pose, "\n\n")
print("TOTAL MOVEMENT IN Y: ", math.sqrt((self.robot.pose.position.x - initial_position.x) ** 2 + (self.robot.pose.position.y - initial_position.y) ** 2)/ 25.0, "\n")
def update_current_arena_pose(self):
print_debug_header("UPDATING CURRENT POSES")
if (self.robot.pose.origin_id != self.current_robot_pose):
print("WE WERE DELOCALIZED!")
self.localize()
coordinate_systems_diff = -self.pose_offset.degrees
print("Started at arena pose: ", self.current_arena_pose, "\n\n")
#print("Initial robot pose was: ", self.current_robot_pose)
#print("Current robot pose is: ", self.robot.pose)
#print("With a diff heading of: ", coordinate_systems_diff)
d_x, d_y = rotate_point(self.robot.pose.position.x - self.current_robot_pose.position.x, self.robot.pose.position.y - self.current_robot_pose.position.y, coordinate_systems_diff)
#print("Calculated initial arena pose is:", arena_initial_pose_mm)
#arena_final_pose_mm = rotate_point(, self.robot.pose.position.y, coordinate_systems_diff)
#print("Calculated final arena pose is:", arena_final_pose_mm)
#print("COMPUTE ODOMETRY:" ,self.__compute_odometry())
#d_x = arena_final_pose_mm[0] - arena_initial_pose_mm[0]
#d_y = arena_final_pose_mm[1] - arena_initial_pose_mm[1]
d_heading = diff_heading_deg(self.robot.pose.rotation.angle_z.degrees, self.current_robot_pose.rotation.angle_z.degrees)
difference_pose = convertPoseFromMmToInches(Pose(x=d_x, y=d_y, z=0, angle_z=degrees(d_heading)))
print("We think we moved ", difference_pose, "\n\n")
self.current_arena_pose = self.current_arena_pose + difference_pose
self.current_robot_pose = self.robot.pose
print("Current arena pose is now: ", self.current_arena_pose, "\n\n")
async def pick_up_cube(self, tries=5):
print_debug_header("PICKING UP CUBE")
cube = None
turns = [-30, 30, 30, -30] * 20
for t in turns:
try:
cube = await self.robot.world.wait_for_observed_light_cube(timeout=1)
await self.robot.turn_in_place(angle=degrees(t)).wait_for_completed()
if (cube != None):
print("Found a cube! ", cube)
break
except:
continue
if (cube == None):
raise Exception("Could not find cube!")
picked_up_cube = await self.robot.pickup_object(cube, num_retries=tries).wait_for_completed()
self.update_current_arena_pose()
if (picked_up_cube == None):
print("Could not get the cube.")
await self.robot.say_text("Help me!").wait_for_completed()
await self.robot.set_lift_height(1.0).wait_for_completed()
asyncio.sleep(5)
else:
print("Picked up cube!")
async def set_down_cube(self):
print_debug_header("DROPPED")
# Drop the cube
await self.robot.set_lift_height(0.0).wait_for_completed()
await self.robot.set_head_angle(degrees(3)).wait_for_completed()
print("Dropped off at pose ", self.current_drop_off_pose_idx)
# Store the old drop position
old_drop_off_position = self.drop_off_poses[self.current_drop_off_pose_idx].position
# Calculate the next drop position
self.current_drop_off_pose_idx = self.current_drop_off_pose_idx + 1 % 3
new_drop_off_position = self.drop_off_poses[self.current_drop_off_pose_idx].position
# Set the second step to stop perpendicular to the next drop off location
self.drop_off_poses[1] = Pose(x=new_drop_off_position.x, y=old_drop_off_position.y, z=0, angle_z=degrees(90))
# set the drop off location
self.drop_off_poses[2] = self.drop_off_poses[self.current_drop_off_pose_idx]
async def localize(self, turn_angle=20):
print_debug_header("LOCALIZING")
# reset our location estimates
conf = False
self.current_arena_pose = Pose(0,0,0,angle_z=degrees(0))
self.pf = ParticleFilter(self.grid)
# reset lift and head
await self.robot.set_lift_height(0.0).wait_for_completed()
await self.robot.set_head_angle(degrees(3)).wait_for_completed()
while not conf:
# move a little
self.current_robot_pose = self.robot.pose
await self.robot.turn_in_place(angle=degrees(turn_angle)).wait_for_completed()
odometry = self.__compute_odometry()
detected_markers, camera_image = await self.__marker_processing()
# update, motion, and measurment with the odometry and marker data
curr_x, curr_y, curr_h, conf = self.pf.update(odometry, detected_markers)
# update gui
self.gui.show_particles(self.pf.particles)
self.gui.show_mean(curr_x, curr_y, curr_h)
self.gui.show_camera_image(camera_image)
self.gui.updated.set()
self.current_robot_pose = self.robot.pose
self.current_arena_pose = Pose(curr_x , curr_y, 0, angle_z=degrees(curr_h))
self.pose_offset = degrees(-(diff_heading_deg(curr_h, self.robot.pose.rotation.angle_z.degrees)))
print("We localized to arena location ", self.current_arena_pose)
def __compute_odometry(self, cvt_inch=True):
'''
Compute the odometry given the current pose of the robot (use robot.pose)
Input:
- curr_pose: a cozmo.robot.Pose representing the robot's current location
- cvt_inch: converts the odometry into grid units
Returns:
- 3-tuple (dx, dy, dh) representing the odometry
'''
last_x, last_y, last_h = self.current_robot_pose.position.x, self.current_robot_pose.position.y, \
self.current_robot_pose.rotation.angle_z.degrees
curr_x, curr_y, curr_h = self.robot.pose.position.x, self.robot.pose.position.y, \
self.robot.pose.rotation.angle_z.degrees
dx, dy = rotate_point(curr_x-last_x, curr_y-last_y, -last_h)
if cvt_inch:
dx, dy = dx / self.grid.scale, dy / self.grid.scale
return (dx, dy, diff_heading_deg(curr_h, last_h))
async def __marker_processing(self, show_diagnostic_image=False):
'''
Obtain the visible markers from the current frame from Cozmo's camera.
Since this is an async function, it must be called using await, for example:
markers, camera_image = await marker_processing(robot, camera_settings, show_diagnostic_image=False)
Input:
- robot: cozmo.robot.Robot object
- camera_settings: 3x3 matrix representing the camera calibration settings
- show_diagnostic_image: if True, shows what the marker detector sees after processing
Returns:
- a list of detected markers, each being a 3-tuple (rx, ry, rh)
(as expected by the particle filter's measurement update)
- a PIL Image of what Cozmo's camera sees with marker annotations
'''
# Wait for the latest image from Cozmo
image_event = await self.robot.world.wait_for(cozmo.camera.EvtNewRawCameraImage, timeout=30)
# Convert the image to grayscale
image = np.array(image_event.image)
image = color.rgb2gray(image)
# Detect the markers
markers, diag = detect.detect_markers(image, self.camera_settings, include_diagnostics=True)
# Measured marker list for the particle filter, scaled by the grid scale
marker_list = [marker['xyh'] for marker in markers]
marker_list = [(x/self.grid.scale, y/self.grid.scale, h) for x,y,h in marker_list]
# Annotate the camera image with the markers
if not show_diagnostic_image:
annotated_image = image_event.image.resize((image.shape[1] * 2, image.shape[0] * 2))
annotator.annotate_markers(annotated_image, markers, scale=2)
else:
diag_image = color.gray2rgb(diag['filtered_image'])
diag_image = Image.fromarray(np.uint8(diag_image * 255)).resize((image.shape[1] * 2, image.shape[0] * 2))
annotator.annotate_markers(diag_image, markers, scale=2)
annotated_image = diag_image
return marker_list, annotated_image