class RobotControl(object):
"""
Class used to interface with the rover. Gets sensor measurements through ROS subscribers,
and transforms them into the 2D plane, and publishes velocity commands.
"""
def __init__(self, world_map, occupancy_map, pos_init, pos_goal, max_speed,
max_omega, x_spacing, y_spacing, t_cam_to_body):
"""
Initialize the class
"""
# Handles all the ROS related items
self.ros_interface = ROSInterface(t_cam_to_body)
self.kalman_filter = KalmanFilter(world_map)
print("INITSTATE", self.kalman_filter.state)
self.diff_drive_controller = DiffDriveController(max_speed, max_omega)
self.vel = 0
self.omega = 0
self.curInd = 0
self.path = dijkstras(occupancy_map, x_spacing, y_spacing, pos_init,
pos_goal)
print(self.path)
self.curGoal = self.path[0]
self.done = False
def process_measurements(self):
"""
This function is called at 60Hz
"""
meas = self.ros_interface.get_measurements()
print("Mesurements", meas)
imu_meas = self.ros_interface.get_imu()
print(imu_meas)
updatedPosition = self.kalman_filter.step_filter(
self.vel, self.omega, imu_meas, meas)
print(np.linalg.norm(self.curGoal - updatedPosition[0:1]))
if ((np.abs(self.curGoal[0] - updatedPosition[0]) > 0.1)
or (np.abs(self.curGoal[1] - updatedPosition[1]) > 0.1)):
(v, omega, done) = self.diff_drive_controller.compute_vel(
updatedPosition, self.curGoal)
self.vel = v
self.omega = omega
print("commanded vel:", v, omega)
self.ros_interface.command_velocity(v, omega)
else:
print("updating")
self.curInd = self.curInd + 1
if self.curInd < len(self.path):
self.curGoal = self.path[self.curInd]
else:
self.done = True
updatedPosition.shape = (3, 1)
return
class RobotControl(object):
"""
Class used to interface with the rover. Gets sensor measurements through ROS subscribers,
and transforms them into the 2D plane, and publishes velocity commands.
"""
def __init__(self, world_map,occupancy_map, pos_init, pos_goal, max_speed, max_omega, x_spacing, y_spacing, t_cam_to_body):
"""
Initialize the class
Inputs: (all loaded from the parameter YAML file)
world_map - a P by 4 numpy array specifying the location, orientation,
and identification of all the markers/AprilTags in the world. The
format of each row is (x,y,theta,id) with x,y giving 2D position,
theta giving orientation, and id being an integer specifying the
unique identifier of the tag.
occupancy_map - an N by M numpy array of boolean values (represented as
integers of either 0 or 1). This represents the parts of the map
that have obstacles. It is mapped to metric coordinates via
x_spacing and y_spacing
pos_init - a 3 by 1 array specifying the initial position of the robot,
formatted as usual as (x,y,theta)
pos_goal - a 3 by 1 array specifying the final position of the robot,
also formatted as (x,y,theta)
max_speed - a parameter specifying the maximum forward speed the robot
can go (i.e. maximum control signal for v)
max_omega - a parameter specifying the maximum angular speed the robot
can go (i.e. maximum control signal for omega)
x_spacing - a parameter specifying the spacing between adjacent columns
of occupancy_map
y_spacing - a parameter specifying the spacing between adjacent rows
of occupancy_map
t_cam_to_body - numpy transformation between the camera and the robot
(not used in simulation)
"""
# TODO for student: Comment this when running on the robot
self.markers = world_map
self.robot_sim = RobotSim(world_map, occupancy_map, pos_init, pos_goal,
max_speed, max_omega, x_spacing, y_spacing)
self.vel = np.array([0, 0])
self.imu_meas = np.array([])
self.meas = []
# TODO for student: Use this when transferring code to robot
# Handles all the ROS related items
#self.ros_interface = ROSInterface(t_cam_to_body)
# YOUR CODE AFTER THIS
# Uncomment as completed
self.goals = dijkstras(occupancy_map, x_spacing, y_spacing, pos_init, pos_goal)
self.total_goals = self.goals.shape[0]
self.cur_goal = 1
self.kalman_filter = KalmanFilter(world_map)
self.diff_drive_controller = DiffDriveController(max_speed, max_omega)
def process_measurements(self):
"""
YOUR CODE HERE
Main loop of the robot - where all measurements, control, and esimtaiton
are done. This function is called at 60Hz
"""
# TODO for student: Comment this when running on the robot
"""
measurements - a N by 5 list of visible tags or None. The tags are in
the form in the form (x,y,theta,id,time) with x,y being the 2D
position of the marker relative to the robot, theta being the
relative orientation of the marker with respect to the robot, id
being the identifier from the map, and time being the current time
stamp. If no tags are seen, the function returns None.
"""
# meas: measurements coming from tags
meas = self.robot_sim.get_measurements()
self.meas = meas;
# imu_meas: measurment comig from the imu
imu_meas = self.robot_sim.get_imu()
self.imu_meas = imu_meas
pose = self.kalman_filter.step_filter(self.vel, self.imu_meas, np.asarray(self.meas))
self.robot_sim.set_est_state(pose)
# goal = self.goals[self.cur_goal]
# vel = self.diff_drive_controller.compute_vel(pose, goal)
# self.vel = vel[0:2]
# self.robot_sim.command_velocity(vel[0], vel[1])
# close_enough = vel[2]
# if close_enough:
# print 'goal reached'
# if self.cur_goal < (self.total_goals - 1):
# self.cur_goal = self.cur_goal + 1
# vel = (0, 0)
# self.vel = vel
# self.robot_sim.command_velocity(vel[0], vel[1])
# else:
# vel = (0, 0)
# self.vel = vel
# self.robot_sim.command_velocity(vel[0], vel[1])
# Code to follow AprilTags
if(meas != None and meas):
cur_meas = meas[0]
tag_robot_pose = cur_meas[0:3]
tag_world_pose = self.tag_pos(cur_meas[3])
state = self.robot_pos(tag_world_pose, tag_robot_pose)
goal = tag_world_pose
vel = self.diff_drive_controller.compute_vel(pose, goal)
self.vel = vel[0:2];
if(not vel[2]):
self.robot_sim.command_velocity(vel[0], vel[1])
else:
vel = (0.1, 0.1)
self.vel = vel
self.robot_sim.command_velocity(vel[0], vel[1])
else:
vel = (0.1, 0.1)
self.vel = vel
self.robot_sim.command_velocity(vel[0], vel[1])
# goal = [-0.5, 2.5]
# goal = self.goals[self.cur_goal]
# vel = self.diff_drive_controller.compute_vel(pose, goal)
# self.vel = vel[0:2];
# if(not vel[2]):
# self.robot_sim.command_velocity(vel[0], vel[1])
# else:
# vel = (0, 0)
# if self.cur_goal < (self.total_goals - 1):
# self.cur_goal = self.cur_goal + 1
# self.vel = vel
# TODO for student: Use this when transferring code to robot
# meas = self.ros_interface.get_measurements()
# imu_meas = self.ros_interface.get_imu()
return
def tag_pos(self, marker_id):
for i in range(len(self.markers)):
marker_i = np.copy(self.markers[i])
if marker_i[3] == marker_id:
return marker_i[0:3]
return None
def robot_pos(self, w_pos, r_pos):
H_W = np.array([[math.cos(w_pos[2]), -math.sin(w_pos[2]), w_pos[0]],
[math.sin(w_pos[2]), math.cos(w_pos[2]), w_pos[1]],
[0, 0, 1]])
H_R = np.array([[math.cos(r_pos[2]), -math.sin(r_pos[2]), r_pos[0]],
[math.sin(r_pos[2]), math.cos(r_pos[2]), r_pos[1]],
[0, 0, 1]])
w_r = H_W.dot(inv(H_R))
robot_pose = np.array([[w_r[0,2]], [w_r[1,2]], [math.atan2(w_r[1,0], w_r[0, 0])]])
return robot_pose
class RobotControl(object):
"""
Class used to interface with the rover. Gets sensor measurements through ROS subscribers,
and transforms them into the 2D plane, and publishes velocity commands.
"""
def __init__(self, world_map,occupancy_map, pos_init, pos_goal, max_speed, max_omega, x_spacing, y_spacing, t_cam_to_body):
"""
Initialize the class
Inputs: (all loaded from the parameter YAML file)
world_map - a P by 4 numpy array specifying the location, orientation,
and identification of all the markers/AprilTags in the world. The
format of each row is (x,y,theta,id) with x,y giving 2D position,
theta giving orientation, and id being an integer specifying the
unique identifier of the tag.
occupancy_map - an N by M numpy array of boolean values (represented as
integers of either 0 or 1). This represents the parts of the map
that have obstacles. It is mapped to metric coordinates via
x_spacing and y_spacing
pos_init - a 3 by 1 array specifying the initial position of the robot,
formatted as usual as (x,y,theta)
pos_goal - a 3 by 1 array specifying the final position of the robot,
also formatted as (x,y,theta)
max_speed - a parameter specifying the maximum forward speed the robot
can go (i.e. maximum control signal for v)
max_omega - a parameter specifying the maximum angular speed the robot
can go (i.e. maximum control signal for omega)
x_spacing - a parameter specifying the spacing between adjacent columns
of occupancy_map
y_spacing - a parameter specifying the spacing between adjacent rows
of occupancy_map
t_cam_to_body - numpy transformation between the camera and the robot
(not used in simulation)
"""
# TODO for student: Comment this when running on the robot
self.robot_sim = RobotSim(world_map, occupancy_map, pos_init, pos_goal,
max_speed, max_omega, x_spacing, y_spacing)
# TODO for student: Use this when transferring code to robot
# Handles all the ROS related items
#self.ros_interface = ROSInterface(t_cam_to_body)
# Uncomment as completed
self.kalman_filter = KalmanFilter(world_map)
self.diff_drive_controller = DiffDriveController(max_speed, max_omega)
plan = dijkstras(occupancy_map, x_spacing, y_spacing, pos_init, pos_goal)
self.state_tol = 0.1
self.path = plan.tolist()
print "Path: ", self.path, type(self.path)
self.path.reverse()
self.path.pop()
self.state = pos_init
self.goal = self.path.pop()
self.x_offset = x_spacing
self.vw = (0, 0, False)
# self.goal[0] += self.x_offset/2
# self.goal[1] += y_spacing
print "INIT GOAL: ", self.goal
# def dijkstras(occupancy_map, x_spacing, y_spacing, start, goal):
def process_measurements(self):
"""
Main loop of the robot - where all measurements, control, and estimation
are done. This function is called at 60Hz
"""
meas = self.robot_sim.get_measurements()
imu_meas = self.robot_sim.get_imu()
self.vw = self.diff_drive_controller.compute_vel(self.state, self.goal)
print "VW: ", self.vw
print "Running Controller."
if self.vw[2] == False:
self.robot_sim.command_velocity(self.vw[0], self.vw[1])
else:
self.robot_sim.command_velocity(0, 0)
est_x = self.kalman_filter.step_filter(self.vw, imu_meas, meas)
print "EST X: ", est_x, est_x[2][0]
if est_x[2][0] > 2.617991667:
est_x[2][0] = 2.617991667
if est_x[2][0] < 0.523598333:
est_x[2][0] = 0.523598333
self.state = est_x
print "Get GT Pose: ", self.robot_sim.get_gt_pose()
print "EKF Pose: ", est_x
self.robot_sim.get_gt_pose()
self.robot_sim.set_est_state(est_x)
if imu_meas != None:
self.kalman_filter.prediction(self.vw, imu_meas)
if meas != None and meas != []:
print("Measurements: ", meas)
if imu_meas != None:
# self.kalman_filter.prediction(self.vw, imu_meas)
self.kalman_filter.update(meas)
pos_x_check = ((self.goal[0] + self.state_tol) > est_x.item(0)) and \
((self.goal[0] - self.state_tol) < est_x.item(0))
pos_y_check = ((self.goal[1] + self.state_tol) > est_x.item(1)) and \
((self.goal[1] - self.state_tol) < est_x.item(1))
if pos_x_check and pos_y_check:
if self.path != []:
self.goal = self.path.pop()
# self.goal[0] += self.x_offset/2
# self.goal[1] += y_spacing
else:
self.goal = est_x
class RobotControl(object):
"""
Class used to interface with the rover. Gets sensor measurements through ROS subscribers,
and transforms them into the 2D plane, and publishes velocity commands.
"""
def __init__(self, world_map, occupancy_map, pos_init, pos_goal, max_speed,
max_omega, x_spacing, y_spacing, t_cam_to_body):
"""
Initialize the class
Inputs: (all loaded from the parameter YAML file)
world_map - a P by 4 numpy array specifying the location, orientation,
and identification of all the markers/AprilTags in the world. The
format of each row is (x,y,theta,id) with x,y giving 2D position,
theta giving orientation, and id being an integer specifying the
unique identifier of the tag.
occupancy_map - an N by M numpy array of boolean values (represented as
integers of either 0 or 1). This represents the parts of the map
that have obstacles. It is mapped to metric coordinates via
x_spacing and y_spacing
pos_init - a 3 by 1 array specifying the initial position of the robot,
formatted as usual as (x,y,theta)
pos_goal - a 3 by 1 array specifying the final position of the robot,
also formatted as (x,y,theta)
max_speed - a parameter specifying the maximum forward speed the robot
can go (i.e. maximum control signal for v)
max_omega - a parameter specifying the maximum angular speed the robot
can go (i.e. maximum control signal for omega)
x_spacing - a parameter specifying the spacing between adjacent columns
of occupancy_map
y_spacing - a parameter specifying the spacing between adjacent rows
of occupancy_map
t_cam_to_body - numpy transformation between the camera and the robot
(not used in simulation)
"""
# Handles all the ROS related items
self.ros_interface = ROSInterface(t_cam_to_body)
self.kalman_filter = KalmanFilter(world_map)
self.prev_v = 0
self.est_pose = np.array([[0], [0], [0]])
self.diff_drive_controller = DiffDriveController(max_speed, max_omega)
self.prev_imu_meas = np.array([[0], [0], [0], [0], [0]])
def process_measurements(self, waypoint):
"""
waypoint is a 1D list [x,y] containing the next waypoint the rover needs to go
YOUR CODE HERE
Main loop of the robot - where all measurements, control, and esimtaiton
are done. This function is called at 60Hz
"""
#This gives the xy location and the orientation of the tag in the rover frame
#The orientation is zero when the rover faces directly at the tag
meas = self.ros_interface.get_measurements()
self.est_pose = self.kalman_filter.step_filter(self.prev_v,
self.prev_imu_meas,
meas)
state = [self.est_pose[0, 0], self.est_pose[1, 0], self.est_pose[2, 0]]
goal = [waypoint[0], waypoint[1]]
controls = self.diff_drive_controller.compute_vel(state, goal)
self.ros_interface.command_velocity(controls[0], controls[1])
self.prev_v = controls[0]
imu_meas = self.ros_interface.get_imu()
if imu_meas != None:
imu_meas[3, 0] = -imu_meas[
3, 0] #clockwise angular vel is positive from IMU
self.prev_imu_meas = imu_meas
return controls[2]
class RobotControl(object):
"""
Class used to interface with the rover. Gets sensor measurements through ROS subscribers,
and transforms them into the 2D plane, and publishes velocity commands.
"""
def __init__(self, world_map, occupancy_map, pos_init, pos_goal, max_speed,
max_omega, x_spacing, y_spacing, t_cam_to_body):
"""
Initialize the class
Inputs: (all loaded from the parameter YAML file)
world_map - a P by 4 numpy array specifying the location, orientation,
and identification of all the markers/AprilTags in the world. The
format of each row is (x,y,theta,id) with x,y giving 2D position,
theta giving orientation, and id being an integer specifying the
unique identifier of the tag.
occupancy_map - an N by M numpy array of boolean values (represented as
integers of either 0 or 1). This represents the parts of the map
that have obstacles. It is mapped to metric coordinates via
x_spacing and y_spacing
pos_init - a 3 by 1 array specifying the initial position of the robot,
formatted as usual as (x,y,theta)
pos_goal - a 3 by 1 array specifying the final position of the robot,
also formatted as (x,y,theta)
max_speed - a parameter specifying the maximum forward speed the robot
can go (i.e. maximum control signal for v)
max_omega - a parameter specifying the maximum angular speed the robot
can go (i.e. maximum control signal for omega)
x_spacing - a parameter specifying the spacing between adjacent columns
of occupancy_map
y_spacing - a parameter specifying the spacing between adjacent rows
of occupancy_map
t_cam_to_body - numpy transformation between the camera and the robot
(not used in simulation)
"""
# TODO for student: Comment this when running on the robot
#self.robot_sim = RobotSim(world_map, occupancy_map, pos_init, pos_goal,
# max_speed, max_omega, x_spacing, y_spacing)
# TODO for student: Use this when transferring code to robot
# Handles all the ROS related items
self.ros_interface = ROSInterface(t_cam_to_body)
# YOUR CODE AFTER THIS
# speed control variables
self.v = 0.1 # allows persistent cmds through detection misses
self.omega = -0.1 # allows persistent cmds through detection misses
self.last_detect_time = rospy.get_time() #TODO on bot only
self.missed_vision_debounce = 1
self.start_time = 0
# generate the path assuming we know our start location, goal, and environment
self.path = dijkstras(occupancy_map, x_spacing, y_spacing, pos_init,
pos_goal)
self.path_idx = 0
self.mission_complete = False
self.carrot_distance = 0.22
# Uncomment as completed
self.kalman_filter = KalmanFilter(world_map)
self.diff_drive_controller = DiffDriveController(max_speed, max_omega)
def process_measurements(self):
"""
YOUR CODE HERE
Main loop of the robot - where all measurements, control, and esimtaiton
are done. This function is called at 60Hz
"""
print(' ')
# TODO for student: Comment this when running on the robot
#meas = self.robot_sim.get_measurements()
#imu_meas = self.robot_sim.get_imu()
# TODO for student: Use this when transferring code to robot
meas = self.ros_interface.get_measurements()
imu_meas = self.ros_interface.get_imu()
# meas is the position of the robot with respect to the AprilTags
# print(meas)
# now that we have the measurements, update the predicted state
self.kalman_filter.step_filter(self.v, imu_meas, meas)
# print(self.kalman_filter.x_t)
# TODO remove on bot, shows predicted state on simulator
#self.robot_sim.set_est_state(self.kalman_filter.x_t)
# pull the next path point from the list
cur_goal = self.getCarrot()
# cur_goal = self.path[self.path_idx]
# TODO test to just go to a goal
# cur_goal[0] = 0.43
# cur_goal[1] = 2
# calculate the control commands need to reach next path point
#print('')
#print('current goal:')
#print(cur_goal)
#print('current state:')
#print(self.kalman_filter.x_t)
control_cmd = self.diff_drive_controller.compute_vel(
self.kalman_filter.x_t, cur_goal)
self.v = control_cmd[0]
self.omega = control_cmd[1]
#print('control command:')
# print(control_cmd)
if self.mission_complete:
self.v = 0
self.omega = 0
#print(control_cmd)
if control_cmd[2]:
if len(self.path) > (self.path_idx + 1):
self.path_idx = self.path_idx + 1
print('next goal')
else:
self.mission_complete = True
#TODO calibration test on bot only for linear velocity
'''
if self.start_time - 0 < 0.0001:
self.start_time = rospy.get_time()
if(rospy.get_time() - self.start_time > 4):
self.v = 0
self.omega = 0
else:
self.v = 0.15
self.omega = 0
'''
#TODO on bot only
self.ros_interface.command_velocity(self.v, self.omega)
#TODO for simulation
#self.robot_sim.command_velocity(self.v,self.omega)
return
def getCarrot(self):
'''
getCarrot - generates an artificial goal location along a path out
infront of the robot.
path - the set of points which make up the waypoints in the path
position - the current position of the robot
'''
path = self.path
idx = self.path_idx
pos = self.kalman_filter.x_t
# if the current line segment ends in the goal point, set that to the goal
if self.path_idx + 1 == len(self.path):
return self.path[(len(self.path) - 1)]
else:
# find the point on the current line closest to the robot
# calculate current line's slope and intercept
pt1 = self.path[self.path_idx]
pt2 = self.path[self.path_idx + 1]
x_diff = pt2[0] - pt1[0]
y_diff = pt2[1] - pt1[1]
vert = abs(x_diff) < 0.001
# using the current line's slope and intercept find the point on that
# line closest to the robots current point
# assumes all lines are either veritcal or horizontal
x_bot = pos[0][0]
y_bot = pos[1][0]
if vert:
x_norm = pt2[0]
y_norm = y_bot
else:
x_norm = x_bot
y_norm = pt2[1]
# if the normal point is past the end point of this segment inc path idx
# assumes all lines are either vertical or horizontal
inc = False
if vert:
if (y_diff > 0 and y_norm > pt2[1]) or (y_diff < 0
and y_norm < pt2[1]):
inc = True
else:
if (x_diff > 0 and x_norm > pt2[0]) or (x_diff < 0
and x_norm < pt2[0]):
inc = True
if (inc):
self.path_idx = self.path_idx + 1
print('increment path index')
# find a point L distance infront of the normal point on this line
# assumes all lines are either vertical or horizontal
if vert:
x_goal = pt2[0]
if y_diff > 0:
y_goal = y_bot + self.carrot_distance
else:
y_goal = y_bot - self.carrot_distance
else:
y_goal = pt2[1]
if x_diff > 0:
x_goal = x_bot + self.carrot_distance
else:
x_goal = x_bot - self.carrot_distance
goal = np.array([x_goal, y_goal])
#print(goal)
return goal
class RobotControl(object):
"""
Class used to interface with the rover. Gets sensor measurements through ROS subscribers,
and transforms them into the 2D plane, and publishes velocity commands.
"""
def __init__(self, world_map, occupancy_map, pos_init, pos_goal, max_speed,
max_omega, x_spacing, y_spacing, t_cam_to_body):
"""
Initialize the class
Inputs: (all loaded from the parameter YAML file)
world_map - a P by 4 numpy array specifying the location, orientation,
and identification of all the markers/AprilTags in the world. The
format of each row is (x,y,theta,id) with x,y giving 2D position,
theta giving orientation, and id being an integer specifying the
unique identifier of the tag.
occupancy_map - an N by M numpy array of boolean values (represented as
integers of either 0 or 1). This represents the parts of the map
that have obstacles. It is mapped to metric coordinates via
x_spacing and y_spacing
pos_init - a 3 by 1 array specifying the initial position of the robot,
formatted as usual as (x,y,theta)
pos_goal - a 3 by 1 array specifying the final position of the robot,
also formatted as (x,y,theta)
max_speed - a parameter specifying the maximum forward speed the robot
can go (i.e. maximum control signal for v)
max_omega - a parameter specifying the maximum angular speed the robot
can go (i.e. maximum control signal for omega)
x_spacing - a parameter specifying the spacing between adjacent columns
of occupancy_map
y_spacing - a parameter specifying the spacing between adjacent rows
of occupancy_map
t_cam_to_body - numpy transformation between the camera and the robot
(not used in simulation)
"""
# TODO for student: Comment this when running on the robot
self.robot_sim = RobotSim(world_map, occupancy_map, pos_init, pos_goal,
max_speed, max_omega, x_spacing, y_spacing)
# TODO for student: Use this when transferring code to robot
# Handles all the ROS related items
#self.ros_interface = ROSInterface(t_cam_to_body)
# YOUR CODE AFTER THIS
self.pos_goal = pos_goal
self.world_map = world_map
self.vel = np.array([0., 0.])
self.imu_meas = np.array([])
self.meas = []
self.max_speed = max_speed
self.max_omega = max_omega
self.goals = dijkstras(occupancy_map, x_spacing, y_spacing, pos_init,
pos_goal)
# print(self.goals)
self.total_goals = self.goals.shape[0]
self.cur_goal = 2
self.end_goal = self.goals.shape[0] - 1
self.est_pose = None
# Uncomment as completed
self.kalman_filter = KalmanFilter(world_map)
self.diff_drive_controller = DiffDriveController(max_speed, max_omega)
def process_measurements(self):
"""
YOUR CODE HERE
Main loop of the robot - where all measurements, control, and esimtaiton
are done. This function is called at 60Hz
"""
# TODO for student: Comment this when running on the robot
meas = self.robot_sim.get_measurements()
imu_meas = self.robot_sim.get_imu()
# TODO for student: Use this when transferring code to robot
# meas = self.ros_interface.get_measurements()
# imu_meas = self.ros_interface.get_imu()
self.est_pose = self.kalman_filter.step_filter(self.vel, imu_meas,
np.asarray(meas))
# print(self.est_pose)
# set goal
# print(self.cur_goal)
self.pos_goal = self.goals[self.cur_goal]
# get command
v, w, done = self.diff_drive_controller.compute_vel(
self.est_pose, self.pos_goal)
# while not at goal (waypoint), command velocity
if done:
v, w = (0, 0)
if self.cur_goal < self.end_goal:
self.cur_goal = self.cur_goal + 1
done = False
#self.ros_interface.command_velocity(v,w)
self.robot_sim.command_velocity(v, w)
self.robot_sim.done = done
self.vel = np.array([v, w])
# print(done)
return
class RobotControl(object):
"""Class used to interface with the rover. Gets sensor measurements
through ROS subscribers, and transforms them into the 2D plane,
and publishes velocity commands.
"""
def __init__(self, markers, occupancy_map, pos_init, pos_goal, max_speed,
min_speed, max_omega, x_spacing, y_spacing, t_cam_to_body,
mode):
"""
Initialize the class
"""
# plan a path around obstacles using dijkstra's algorithm
print('Planning path...')
path = findShortestPath(occupancy_map,
x_spacing,
y_spacing,
pos_init[0:2],
pos_goal[0:2],
dilate=2)
print('Done!')
self.path_manager = PathManager(path)
self.kalman_filter = KalmanFilter(markers, pos_init)
self.diff_drive_controller = DiffDriveController(
max_speed, min_speed, max_omega)
if 'HARDWARE' in mode:
# Handles all the ROS related items
self.ros_interface = ROSInterface(t_cam_to_body)
elif 'SIMULATE' in mode:
self.robot_sim = RobotSim(markers, occupancy_map, pos_init,
pos_goal, max_speed, max_omega,
x_spacing, y_spacing,
self.path_manager.path, mode)
self.user_control = UserControl()
self.vel = 0 # save velocity to use for kalman filter
self.goal = self.path_manager.getNextWaypoint() # get first waypoint
# for logging postion data to csv file
self.stateSaved = []
self.tagsSaved = []
self.waypoints = []
def process_measurements(self):
"""Main loop of the robot - where all measurements, control, and
estimation are done.
"""
v, omega, wayptReached = self.user_control.compute_vel()
self.robot_sim.command_velocity(v, omega)
return
#meas = None # for testing purposes
#imu_meas = None # for testing purpose
#pdb.set_trace()
if (imu_meas is None) and (meas is None):
pass
else:
state = self.kalman_filter.step_filter(self.vel, imu_meas, meas)
if 'SIMULATE' in mode:
self.robot_sim.set_est_state(state)
#print("X = {} cm, Y = {} cm, Theta = {} deg".format(100*state[0],100*state[1],state[2]*180/np.pi))
# save the estimated state and tag statuses for offline animation
self.stateSaved.append(state)
self.waypoints.append(self.path_manager.getActiveWaypointsPos())
if meas is None:
self.tagsSaved.append(None)
else:
meas = np.array(meas)
tagIDs = [int(i) for i in meas[:, 3]]
self.tagsSaved.append(tagIDs)
v, omega, wayptReached = self.diff_drive_controller.compute_vel(
state, self.goal.pos)
self.vel = v
if wayptReached:
self.goal = self.path_manager.getNextWaypoint()
self.diff_drive_controller.done = False # reset diff controller status
if self.goal is None:
print('Goal has been reached!')
np.savez('savedState.npz',
stateSaved=self.stateSaved,
tagsSaved=self.tagsSaved,
waypoints=self.waypoints)
print('Position data saved!')
if 'HARDWARE' in mode:
self.ros_interface.command_velocity(0, 0)
elif 'SIMULATE' in mode:
self.robot_sim.command_velocity(0, 0)
self.robot_sim.done = True
return
else:
if 'HARDWARE' in mode:
self.ros_interface.command_velocity(self.vel, omega)
elif 'SIMULATE' in mode:
self.robot_sim.command_velocity(self.vel, omega)
return
def myhook():
print "shutdown time!"
class RobotControl(object):
"""
Class used to interface with the rover. Gets sensor measurements through ROS subscribers,
and transforms them into the 2D plane, and publishes velocity commands.
"""
def __init__(self, world_map,occupancy_map, pos_init, pos_goal, max_speed, max_omega, x_spacing, y_spacing, t_cam_to_body, sample_time):
"""
Initialize the class
Inputs: (all loaded from the parameter YAML file)
world_map - a P by 4 numpy array specifying the location, orientation,
and identification of all the markers/AprilTags in the world. The
format of each row is (x,y,theta,id) with x,y giving 2D position,
theta giving orientation, and id being an integer specifying the
unique identifier of the tag.
occupancy_map - an N by M numpy array of boolean values (represented as
integers of either 0 or 1). This represents the parts of the map
that have obstacles. It is mapped to metric coordinates via
x_spacing and y_spacing
pos_init - a 3 by 1 array specifying the initial position of the robot,
formatted as usual as (x,y,theta)
pos_goal - a 3 by 1 array specifying the final position of the robot,
also formatted as (x,y,theta)
max_speed - a parameter specifying the maximum forward speed the robot
can go (i.e. maximum control signal for v)
max_omega - a parameter specifying the maximum angular speed the robot
can go (i.e. maximum control signal for omega)
x_spacing - a parameter specifying the spacing between adjacent columns
of occupancy_map
y_spacing - a parameter specifying the spacing between adjacent rows
of occupancy_map
t_cam_to_body - numpy transformation between the camera and the robot
(not used in simulation)
sample_time - the sample time in seconds between each measurement (added by me)
"""
# TODO for student: Comment this when running on the robot
self.robot_sim = RobotSim(world_map, occupancy_map, pos_init, pos_goal,
max_speed, max_omega, x_spacing, y_spacing)
# TODO for student: Use this when transferring code to robot
# Handles all the ROS related items
#self.ros_interface = ROSInterface(t_cam_to_body)
# YOUR CODE AFTER THIS
# Uncomment as completed
self.kalman_filter = KalmanFilter(world_map, sample_time)
self.diff_drive_controller = DiffDriveController(max_speed, max_omega)
self.v_last = 0.0
self.omega_last = 0.0
def process_measurements(self, goal):
"""
YOUR CODE HERE
Main loop of the robot - where all measurements, control, and esimtaiton
are done. This function is called at 60Hz
"""
# TODO for student: Comment this when running on the robot
meas = np.array(self.robot_sim.get_measurements()) # measured pose of tag in robot frame (x,y,theta,id,time)
imu_meas = self.robot_sim.get_imu() # 5 by 1 numpy vector (acc_x, acc_y, acc_z, omega, time)
# Do KalmanFilter step
# Note: The imu_meas could be None if it is sampled at a lower rate than the integration time step.
# For the simulation, assume that imu_meas will always return a valid value because we control it in RobotSim.py.
# For running on the robot, you should include protection for potentially bad measurements.
pose_est = self.kalman_filter.step_filter(self.v_last, imu_meas, meas)
at_goal = False
v, omega, at_goal = self.diff_drive_controller.compute_vel(pose_est, goal)
self.robot_sim.command_velocity(v, omega)
self.v_last = v
self.omega_last = omega
#print("estimated state = ", est_state)
#print("true state = ", self.robot_sim.get_gt_pose())
# Draw ghost robot
est_state = np.array([[pose_est[0]],[pose_est[1]],[pose_est[2]]])
self.robot_sim.set_est_state(est_state)
# TODO for student: Use this when transferring code to robot
# meas = self.ros_interface.get_measurements()
# imu_meas = self.ros_interface.get_imu()
return at_goal
class RobotControl(object):
"""
Class used to interface with the rover. Gets sensor measurements through ROS subscribers,
and transforms them into the 2D plane, and publishes velocity commands.
"""
def __init__(self, world_map,occupancy_map, pos_init, pos_goal, max_speed, max_omega, x_spacing, y_spacing, t_cam_to_body):
"""
Initialize the class
Inputs: (all loaded from the parameter YAML file)
world_map - a P by 4 numpy array specifying the location, orientation,
and identification of all the markers/AprilTags in the world. The
format of each row is (x,y,theta,id) with x,y giving 2D position,
theta giving orientation, and id being an integer specifying the
unique identifier of the tag.
occupancy_map - an N by M numpy array of boolean values (represented as
integers of either 0 or 1). This represents the parts of the map
that have obstacles. It is mapped to metric coordinates via
x_spacing and y_spacing
pos_init - a 3 by 1 array specifying the initial position of the robot,
formatted as usual as (x,y,theta)
pos_goal - a 3 by 1 array specifying the final position of the robot,
also formatted as (x,y,theta)
max_speed - a parameter specifying the maximum forward speed the robot
can go (i.e. maximum control signal for v)
max_omega - a parameter specifying the maximum angular speed the robot
can go (i.e. maximum control signal for omega)
x_spacing - a parameter specifying the spacing between adjacent columns
of occupancy_map
y_spacing - a parameter specifying the spacing between adjacent rows
of occupancy_map
t_cam_to_body - numpy transformation between the camera and the robot
(not used in simulation)
"""
# TODO for student: Comment this when running on the robot
self.robot_sim = RobotSim(world_map, occupancy_map, pos_init, pos_goal,
max_speed, max_omega, x_spacing, y_spacing)
# TODO for student: Use this when transferring code to robot
# Handles all the ROS related items
#self.ros_interface = ROSInterface(t_cam_to_body)
# YOUR CODE AFTER THIS
# Uncomment as completed
self.kalman_filter = KalmanFilter(world_map)
self.diff_drive_controller = DiffDriveController(max_speed, max_omega)
self.v_last = 0.0
self.omega_last = 0.0
def process_measurements(self):
"""
YOUR CODE HERE
Main loop of the robot - where all measurements, control, and esimtaiton
are done. This function is called at 60Hz
"""
# TODO for student: Comment this when running on the robot
meas = np.array(self.robot_sim.get_measurements()) # tag wrt robot in robot frame (x,y,theta,id,time)
imu_meas = self.robot_sim.get_imu() # (5,1) np array (xacc,yacc,zacc,omega,time)
done = False
goal = np.array([1., 1.2])
# z_t is the Nx4 numpy array (x,y,theta,id) of tag wrt robot
if meas is not None and meas != []:
#print(meas)
#print(imu_meas)
z_t = meas[:,:-1] # (3, 4) np array (x, y, theta, id)
else:
z_t = meas
#print("v_last = ", self.v_last)
#print("imu_meas = ", imu_meas)
#print("z_t = ", z_t)
state = self.kalman_filter.step_filter(self.v_last, self.omega_last, imu_meas, z_t)
#print("estimated state = ", state)
#print("true state = ", self.robot_sim.get_gt_pose())
# Draw ghost robot
est_pose = np.array([[state[0]],[state[1]],[state[2]]])
self.robot_sim.set_est_state(est_pose)
if done is False:
v, omega, done = self.diff_drive_controller.compute_vel(state, goal)
self.robot_sim.command_velocity(v, omega)
self.v_last = v
self.omega_last = omega
#if meas is not None and meas != []:
#print meas
#state = np.array(meas[0][0:3])
#goal = np.array([0, 0])
#v, omega, done = self.diff_drive_controller.compute_vel(state, goal)
#self.robot_sim.command_velocity(v, omega)
# TODO for student: Use this when transferring code to robot
# meas = self.ros_interface.get_measurements()
# imu_meas = self.ros_interface.get_imu()
return done
class RobotControl(object):
"""
Class used to interface with the rover. Gets sensor measurements through ROS subscribers,
and transforms them into the 2D plane, and publishes velocity commands.
"""
def __init__(self, world_map,occupancy_map, pos_init, pos_goal, max_speed, max_omega, x_spacing, y_spacing, t_cam_to_body):
"""
Initialize the class
"""
# Handles all the ROS related items
self.ros_interface = ROSInterface(t_cam_to_body)
# YOUR CODE AFTER THIS
# Uncomment as completed
self.markers = world_map
self.vel = np.array([0, 0])
self.imu_meas = np.array([])
self.meas = []
# TODO for student: Use this when transferring code to robot
# Handles all the ROS related items
#self.ros_interface = ROSInterface(t_cam_to_body)
# YOUR CODE AFTER THIS
# Uncomment as completed
self.goals = dijkstras(occupancy_map, x_spacing, y_spacing, pos_init, pos_goal)
# self.total_goals = self.goals.shape[0]
self.cur_goal = 2
self.end_goal = self.goals.shape[0] - 1
self.kalman_filter = KalmanFilter(world_map)
self.diff_drive_controller = DiffDriveController(max_speed, max_omega)
def process_measurements(self):
"""
YOUR CODE HERE
This function is called at 60Hz
"""
meas = self.ros_interface.get_measurements()
self.meas = meas;
print 'tag output'
print meas
# imu_meas: measurment comig from the imu
imu_meas = self.ros_interface.get_imu()
self.imu_meas = imu_meas
print 'imu measurement'
print imu_meas
pose = self.kalman_filter.step_filter(self.vel, self.imu_meas, np.asarray(self.meas))
# Code to follow AprilTags
'''
if(meas != None and meas):
cur_meas = meas[0]
tag_robot_pose = cur_meas[0:3]
tag_world_pose = self.tag_pos(cur_meas[3])
state = self.robot_pos(tag_world_pose, tag_robot_pose)
goal = tag_world_pose
vel = self.diff_drive_controller.compute_vel(state, goal)
self.vel = vel[0:2];
print vel
if(not vel[2]):
self.ros_interface.command_velocity(vel[0], vel[1])
else:
vel = (0.01, 0.1)
self.vel = vel
self.ros_interface.command_velocity(vel[0], vel[1])
'''
# Code to move autonomously
goal = self.goals[self.cur_goal]
print 'pose'
print pose
print 'goal'
print goal
vel = self.diff_drive_controller.compute_vel(pose, goal)
self.vel = vel[0:2];
print 'speed'
print vel
if(not vel[2]):
self.ros_interface.command_velocity(vel[0], vel[1])
else:
vel = (0, 0)
if self.cur_goal < self.end_goal:
self.cur_goal = self.cur_goal + 1
self.ros_interface.command_velocity(vel[0], vel[1])
self.vel = vel
return
def tag_pos(self, marker_id):
for i in range(len(self.markers)):
marker_i = np.copy(self.markers[i])
if marker_i[3] == marker_id:
return marker_i[0:3]
return None
def robot_pos(self, w_pos, r_pos):
H_W = np.array([[math.cos(w_pos[2]), -math.sin(w_pos[2]), w_pos[0]],
[math.sin(w_pos[2]), math.cos(w_pos[2]), w_pos[1]],
[0, 0, 1]])
H_R = np.array([[math.cos(r_pos[2]), -math.sin(r_pos[2]), r_pos[0]],
[math.sin(r_pos[2]), math.cos(r_pos[2]), r_pos[1]],
[0, 0, 1]])
w_r = H_W.dot(inv(H_R))
robot_pose = np.array([[w_r[0,2]], [w_r[1,2]], [math.atan2(w_r[1,0], w_r[0, 0])]])
return robot_pose
class RobotControl(object):
"""
Class used to interface with the rover. Gets sensor measurements through ROS subscribers,
and transforms them into the 2D plane, and publishes velocity commands.
"""
def __init__(self, world_map, occupancy_map, pos_init, pos_goal, max_speed,
max_omega, x_spacing, y_spacing, t_cam_to_body):
"""
Initialize the class
Inputs: (all loaded from the parameter YAML file)
world_map - a P by 4 numpy array specifying the location, orientation,
and identification of all the markers/AprilTags in the world. The
format of each row is (x,y,theta,id) with x,y giving 2D position,
theta giving orientation, and id being an integer specifying the
unique identifier of the tag.
occupancy_map - an N by M numpy array of boolean values (represented as
integers of either 0 or 1). This represents the parts of the map
that have obstacles. It is mapped to metric coordinates via
x_spacing and y_spacing
pos_init - a 3 by 1 array specifying the initial position of the robot,
formatted as usual as (x,y,theta)
pos_goal - a 3 by 1 array specifying the final position of the robot,
also formatted as (x,y,theta)
max_speed - a parameter specifying the maximum forward speed the robot
can go (i.e. maximum control signal for v)
max_omega - a parameter specifying the maximum angular speed the robot
can go (i.e. maximum control signal for omega)
x_spacing - a parameter specifying the spacing between adjacent columns
of occupancy_map
y_spacing - a parameter specifying the spacing between adjacent rows
of occupancy_map
t_cam_to_body - numpy transformation between the camera and the robot
(not used in simulation)
"""
# TODO for student: Comment this when running on the robot
self.markers = world_map
self.robot_sim = RobotSim(world_map, occupancy_map, pos_init, pos_goal,
max_speed, max_omega, x_spacing, y_spacing)
self.vel = np.array([0, 0])
self.imu_meas = np.array([])
self.meas = []
# TODO for student: Use this when transferring code to robot
# Handles all the ROS related items
#self.ros_interface = ROSInterface(t_cam_to_body)
# YOUR CODE AFTER THIS
# Uncomment as completed
self.goals = dijkstras(occupancy_map, x_spacing, y_spacing, pos_init,
pos_goal)
self.total_goals = self.goals.shape[0]
self.cur_goal = 1
self.kalman_filter = KalmanFilter(world_map)
self.diff_drive_controller = DiffDriveController(max_speed, max_omega)
def process_measurements(self):
"""
YOUR CODE HERE
Main loop of the robot - where all measurements, control, and esimtaiton
are done. This function is called at 60Hz
"""
# TODO for student: Comment this when running on the robot
"""
measurements - a N by 5 list of visible tags or None. The tags are in
the form in the form (x,y,theta,id,time) with x,y being the 2D
position of the marker relative to the robot, theta being the
relative orientation of the marker with respect to the robot, id
being the identifier from the map, and time being the current time
stamp. If no tags are seen, the function returns None.
"""
# meas: measurements coming from tags
meas = self.robot_sim.get_measurements()
self.meas = meas
# imu_meas: measurment comig from the imu
imu_meas = self.robot_sim.get_imu()
self.imu_meas = imu_meas
pose = self.kalman_filter.step_filter(self.vel, self.imu_meas,
np.asarray(self.meas))
self.robot_sim.set_est_state(pose)
# goal = self.goals[self.cur_goal]
# vel = self.diff_drive_controller.compute_vel(pose, goal)
# self.vel = vel[0:2]
# self.robot_sim.command_velocity(vel[0], vel[1])
# close_enough = vel[2]
# if close_enough:
# print 'goal reached'
# if self.cur_goal < (self.total_goals - 1):
# self.cur_goal = self.cur_goal + 1
# vel = (0, 0)
# self.vel = vel
# self.robot_sim.command_velocity(vel[0], vel[1])
# else:
# vel = (0, 0)
# self.vel = vel
# self.robot_sim.command_velocity(vel[0], vel[1])
# Code to follow AprilTags
if (meas != None and meas):
cur_meas = meas[0]
tag_robot_pose = cur_meas[0:3]
tag_world_pose = self.tag_pos(cur_meas[3])
state = self.robot_pos(tag_world_pose, tag_robot_pose)
goal = tag_world_pose
vel = self.diff_drive_controller.compute_vel(pose, goal)
self.vel = vel[0:2]
if (not vel[2]):
self.robot_sim.command_velocity(vel[0], vel[1])
else:
vel = (0.1, 0.1)
self.vel = vel
self.robot_sim.command_velocity(vel[0], vel[1])
else:
vel = (0.1, 0.1)
self.vel = vel
self.robot_sim.command_velocity(vel[0], vel[1])
# goal = [-0.5, 2.5]
# goal = self.goals[self.cur_goal]
# vel = self.diff_drive_controller.compute_vel(pose, goal)
# self.vel = vel[0:2];
# if(not vel[2]):
# self.robot_sim.command_velocity(vel[0], vel[1])
# else:
# vel = (0, 0)
# if self.cur_goal < (self.total_goals - 1):
# self.cur_goal = self.cur_goal + 1
# self.vel = vel
# TODO for student: Use this when transferring code to robot
# meas = self.ros_interface.get_measurements()
# imu_meas = self.ros_interface.get_imu()
return
def tag_pos(self, marker_id):
for i in range(len(self.markers)):
marker_i = np.copy(self.markers[i])
if marker_i[3] == marker_id:
return marker_i[0:3]
return None
def robot_pos(self, w_pos, r_pos):
H_W = np.array([[math.cos(w_pos[2]), -math.sin(w_pos[2]), w_pos[0]],
[math.sin(w_pos[2]),
math.cos(w_pos[2]), w_pos[1]], [0, 0, 1]])
H_R = np.array([[math.cos(r_pos[2]), -math.sin(r_pos[2]), r_pos[0]],
[math.sin(r_pos[2]),
math.cos(r_pos[2]), r_pos[1]], [0, 0, 1]])
w_r = H_W.dot(inv(H_R))
robot_pose = np.array([[w_r[0, 2]], [w_r[1, 2]],
[math.atan2(w_r[1, 0], w_r[0, 0])]])
return robot_pose
class RobotControl(object):
"""
Class used to interface with the rover. Gets sensor measurements through ROS subscribers,
and transforms them into the 2D plane, and publishes velocity commands.
"""
def __init__(self, world_map, occupancy_map, pos_init, pos_goal, max_speed,
max_omega, x_spacing, y_spacing, t_cam_to_body):
"""
Initialize the class
"""
# Handles all the ROS related items
self.ros_interface = ROSInterface(t_cam_to_body)
self.pos_goal = pos_goal
# YOUR CODE AFTER THIS
#-------------------------------------------#
self.time = rospy.get_time()
self.controlOut = (0.0, 0.0, False)
self.count_noMeasurement = 0
#-------------------------------------------#
self.markers = world_map
self.idx_target_marker = 0
# Calculate the optimal path
# From pos_init to pos_goal
self.path_2D = dijkstras(occupancy_map, x_spacing, y_spacing, pos_init,
pos_goal)
self.idx_path = 0
self.size_path = self.path_2D.shape[0]
print "path.shape[0]", self.size_path
# Generate the 3D path (include "theta")
self.path = np.zeros((self.size_path, 3))
theta = 0.0
for idx in range(self.size_path - 1):
delta = self.path_2D[(idx + 1), :] - self.path_2D[idx, :]
theta = atan2(delta[1], delta[0])
if theta > np.pi:
theta -= np.pi * 2
elif theta < -np.pi:
theta += np.pi * 2
self.path[idx, :] = np.concatenate(
(self.path_2D[idx, :], np.array([theta])), axis=1)
self.path[self.size_path - 1, 0:2] = self.path_2D[self.size_path - 1,
0:2]
self.path[self.size_path - 1, 2] = pos_goal[2] # theta
#
self.path[0, 2] = pos_init[2] # theta
print "3D path:"
print self.path
# Uncomment as completed
# Kalman filter
self.kalman_filter = KalmanFilter(world_map)
self.kalman_filter.mu_est = pos_init # 3*pos_init # For test
# Differential drive
self.diff_drive_controller = DiffDriveController(max_speed, max_omega)
self.wayPointFollowing = wayPointFollowing(max_speed, max_omega)
#
self.task_done = False
def process_measurements(self):
"""
YOUR CODE HERE
This function is called at 60Hz
"""
meas = self.ros_interface.get_measurements()
imu_meas = self.ros_interface.get_imu()
# print 'meas',meas
print 'imu_meas', imu_meas
"""
# Control the robot to track the tag
if (meas is None) or (meas == []):
# stop
# self.ros_interface.command_velocity(0.0,0.0)
#
if self.count_noMeasurement > 30:
# Actually the ros_interface will stop the motor itself if we don't keep sending new commands
self.ros_interface.command_velocity(0.0,0.0)
else:
# Keep the old command
self.ros_interface.command_velocity(self.controlOut[0],self.controlOut[1])
self.count_noMeasurement += 1
else:
print 'meas',meas
self.count_noMeasurement = 0
# Thew differential drive controller that lead the robot to the tag
self.controlOut = self.diff_drive_controller.compute_vel((-1)*np.array(meas[0][0:3]),np.array([0.0,0.0,0.0]))
self.ros_interface.command_velocity(self.controlOut[0],self.controlOut[1])
(v,omega,done) = (self.controlOut[0], self.controlOut[1],False )
"""
"""
if (rospy.get_time() - self.time) < 1.0:
self.ros_interface.command_velocity(0.0, 3.0)
# Linear velocity = 0.3 m/s, Angular velocity = 0.5 rad/s
else:
self.ros_interface.command_velocity(0.0,0.0)
"""
"""
(v,omega,done) = (0.0, 0.0, False)
self.ros_interface.command_velocity(v, omega)
"""
"""
# Directly move to the goal position
if self.controlOut[2]: # done
self.ros_interface.command_velocity(0.0, 0.0)
else:
self.controlOut = self.wayPointFollowing.compute_vel(self.kalman_filter.mu_est, self.pos_goal )
# self.controlOut = self.diff_drive_controller.compute_vel(self.kalman_filter.mu_est, self.pos_goal )
if self.controlOut[2]: # done
self.ros_interface.command_velocity(0.0, 0.0)
else:
self.ros_interface.command_velocity(self.controlOut[0], self.controlOut[1])
"""
"""
#----------------------------------------#
# Switch the targets (way-point of the optimal path) and do the position control
# if self.controlOut[2] and self.idx_path == self.size_path-1: # all done
if self.idx_path == self.size_path-1 and self.controlOut[0] < 0.05 and self.controlOut[1] < 0.1 : # all done
self.ros_interface.command_velocity(0.0, 0.0)
else:
self.controlOut = self.diff_drive_controller.compute_vel(self.kalman_filter.mu_est, self.path[self.idx_path,:] )
self.ros_interface.command_velocity(self.controlOut[0], self.controlOut[1])
if self.controlOut[2] and self.idx_path < self.size_path-1: # way-point done
self.idx_path += 1
#----------------------------------------#
"""
#----------------------------------------#
print "self.idx_path", self.idx_path
# Switch the targets (way-point of the optimal path) and do the position control
# way-point following (no reducing speeed when reach a way-point)
# if self.controlOut[2] and self.idx_path == self.size_path-1: # all done
if self.task_done: # all done
self.ros_interface.command_velocity(0.0, 0.0)
elif self.idx_path == self.size_path - 1: # The last one
# Change the threshold
self.diff_drive_controller.threshold = 0.02 # 3 cm
# Using diff_drive_controller to reach the goal position with right direction
self.controlOut = self.diff_drive_controller.compute_vel(
self.kalman_filter.mu_est, self.path[self.idx_path, :])
# if self.controlOut[0] < 0.05 and self.controlOut[1] < 0.1 : # all done
if self.controlOut[2]: # all done
self.ros_interface.command_velocity(0.0, 0.0)
self.task_done = True # all done
else:
self.ros_interface.command_velocity(self.controlOut[0],
self.controlOut[1])
else:
# The way-points, using wayPointFollowing to trace the trajectory without pausing
if self.idx_path == self.size_path - 2: # The last 2nd one
self.controlOut = self.diff_drive_controller.compute_vel(
self.kalman_filter.mu_est, self.path[self.idx_path, :])
else:
self.controlOut = self.wayPointFollowing.compute_vel(
self.kalman_filter.mu_est, self.path[self.idx_path, :])
# self.controlOut = self.wayPointFollowing.compute_vel(self.kalman_filter.mu_est, self.path[self.idx_path,:] )
self.ros_interface.command_velocity(self.controlOut[0],
self.controlOut[1])
if self.controlOut[
2] and self.idx_path < self.size_path - 1: # way-point done
self.idx_path += 1
#----------------------------------------#
# self.time = rospy.get_time()
# print "self.time",self.time
# Kalman filter
self.kalman_filter.step_filter(self.controlOut[0], (-1) * imu_meas,
meas, rospy.get_time())
print "mu_est", self.kalman_filter.mu_est
return
