RoboRally/remote_control/roborally.py

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# startup:
# roscore -> start ros
# rosparam set cv_camera/device_id 0 -> set appropriate camera device
# rosrun cv_camera cv_camera_node -> start the camera
# roslaunch aruco_detect aruco_detect.launch camera:=cv_camera image:=image_raw dictionary:=16 transport:= fiducial_len:=0.1 # aruco marker detection
# python fiducial_to_2d_pos_angle.py -> compute position and angle of markers in 2d plane
import sys
import rospy
import pygame
import numpy as np
import socket
import scipy.integrate
import copy
import threading
from copy import deepcopy
import matplotlib.pyplot as plt
import matplotlib.animation as anim
import matplotlib.patches as patch
from shapely.geometry import Polygon
import time
from casadi_opt import OpenLoopSolver
from marker_pos_angle.msg import id_pos_angle
from collections import OrderedDict
from argparse import ArgumentParser
MSGLEN = 32
def myreceive(sock):
chunks = []
bytes_recd = 0
while bytes_recd < MSGLEN:
chunk = sock.recv(min(MSGLEN - bytes_recd, 2048))
if chunk == b'':
raise RuntimeError("socket connection broken")
chunks.append(chunk)
bytes_recd = bytes_recd + len(chunk)
if chunk[-1] == '\n':
break
return b''.join(chunks)
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class Robot:
def __init__(self, id, ip):
self.pos = None
self.orient = None
self.grid_pos = (0,0,0)
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self.id = id
self.pos = None
self.euler = None
self.ip = ip
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self.socket = socket.socket()
# variables for measurements
self.tms_0 = None
self.xm_0 = None
self.tms = None
self.xms = None
# currently active control
self.u1 = 0.0
self.u2 = 0.0
def connect(self):
# connect to robot
try:
print("connecting to robot {} with ip {} ...".format(self.id, self.ip))
self.socket.connect((self.ip, 1234)) # connect to robot
print("connected!")
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except socket.error:
print("could not connect to robot {} with ip {}".format(self.id, self.ip))
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sys.exit(1)
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def f_ode(t, x, u):
# dynamical model of the two-wheeled robot
# TODO: find exact values for these parameters
r = 0.03
R = 0.05
d = 0.02
theta = x[2]
omega_r = u[0]
omega_l = u[1]
dx = np.zeros(3)
dx[0] = (r/2.0 * np.cos(theta) - r*d/(2.0*R) * np.sin(theta)) * omega_r \
+ (r/2.0 * np.cos(theta) + r*d/(2.0 * R) * np.sin(theta)) * omega_l
dx[1] = (r/2.0 * np.sin(theta) + r*d/(2.0*R) * np.cos(theta)) * omega_r \
+ (r/2 * np.sin(theta) - r*d/(2.0*R) * np.cos(theta)) * omega_l
dx[2] = -r/(2.0*R) * (omega_r - omega_l)
return dx
class RemoteController:
def __init__(self, id, ip):
self.anim_stopped = False
#self.robots = [Robot(11, '192.168.1.101'), Robot(14, '192.168.1.103')]
self.robots = [Robot(11, '192.168.1.101')]
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#self.robots = [Robot(15, '192.168.1.102')]
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#self.robots = [Robot(id, ip)]
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self.robot_ids = {}
for r in self.robots:
self.robot_ids[r.id] = r
self.valid_cmds = ['forward', 'backward', 'turn left', 'turn right', 'turn around', 'get position', 'set position']
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# socket for movement commands
self.comm_socket = socket.socket()
self.comm_socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
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for robot in self.robots:
robot.connect()
#self.comm_socket.bind((socket.gethostname(), 1337))
self.comm_socket.bind(('', 1337))
self.comm_socket.listen(5)
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self.t = time.time()
# variables for simulated state
self.x0 = None
self.ts = np.array([])
self.xs = []
# variable for mpc open loop
self.ol_x = None
self.ol_y = None
self.mutex = threading.Lock()
# ROS subscriber for detected markers
marker_sub = rospy.Subscriber("/marker_id_pos_angle", id_pos_angle, self.measurement_callback)
# pid parameters
self.controlling = False
# animation
self.fig = plt.figure()
self.ax = self.fig.add_subplot(2,2,1)
self.ax2 = self.fig.add_subplot(2, 2, 2)
self.ax3 = self.fig.add_subplot(2, 2, 4)
self.xdata, self.ydata = [], []
self.line, = self.ax.plot([],[], color='grey', linestyle=':')
self.line_sim, = self.ax.plot([], [])
self.line_ol, = self.ax.plot([],[], color='green', linestyle='--')
self.dirm, = self.ax.plot([], [])
self.dirs, = self.ax.plot([], [])
self.line_x, = self.ax2.plot([],[])
self.line_y, = self.ax3.plot([], [])
self.track_line_inner, = self.ax.plot([], [])
self.track_line_outer, = self.ax.plot([], [])
self.ax.set_xlabel('x-position')
self.ax.set_ylabel('y-position')
self.ax.grid()
self.ax2.set_xlabel('Zeit t')
self.ax2.set_ylabel('x-position')
self.ax2.grid()
self.ax3.set_xlabel('Zeit t')
self.ax3.set_ylabel('y-position')
self.ax3.grid()
self.mstep = 2
self.ols = OpenLoopSolver(N=20, T=1.0)
self.ols.setup()
self.dt = self.ols.T / self.ols.N
self.target = (0.0, 0.0, 0.0)
# integrator
self.r = scipy.integrate.ode(f_ode)
self.omega_max = 5.0
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self.control_scaling = 0.3
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#self.omega_max = 13.32
def ani(self):
print("starting animation")
self.ani = anim.FuncAnimation(self.fig, init_func=self.ani_init, func=self.ani_update, interval=10, blit=True)
plt.ion()
plt.show(block=True)
def ani_init(self):
self.ax.set_xlim(-2, 2)
self.ax.set_ylim(-2, 2)
self.ax.set_aspect('equal', adjustable='box')
self.ax2.set_ylim(-2, 2)
self.ax2.set_xlim(0, 10)
self.ax3.set_ylim(-2, 2)
self.ax3.set_xlim(0, 10)
self.track_line_inner.set_data(self.track.inner_poly.exterior.xy)
self.track_line_outer.set_data(self.track.outer_poly.exterior.xy)
return self.line, self.line_sim, self.dirm, self.dirs, self.line_ol,\
self.track_line_inner, self.track_line_outer, self.line_x,self.line_y,
def ani_update(self, frame):
if self.anim_stopped:
self.ani.event_source.stop()
sys.exit(0)
#print("plotting")
self.mutex.acquire()
try:
# copy data for plot from global arrays
if self.tms is not None:
tm_local = deepcopy(self.tms)
xm_local = deepcopy(self.xms)
if len(tm_local) > 0:
# plot path of the robot
self.line.set_data(xm_local[:,0], xm_local[:,1])
# compute and plot direction the robot is facing
a = xm_local[-1, 0]
b = xm_local[-1, 1]
a2 = a + np.cos(xm_local[-1, 2]) * 0.2
b2 = b + np.sin(xm_local[-1, 2]) * 0.2
self.dirm.set_data(np.array([a, a2]), np.array([b, b2]))
n_plot = 300
if len(tm_local) > n_plot:
# plot x and y coordinate
self.line_x.set_data(tm_local[-n_plot:] - (tm_local[-1] - 10), xm_local[-n_plot:,0])
self.line_y.set_data(tm_local[-n_plot:] - (tm_local[-1] - 10), xm_local[-n_plot:, 1])
ts_local = deepcopy(self.ts)
xs_local = deepcopy(self.xs)
if len(ts_local) > 0:
# plot simulated path of the robot
self.line_sim.set_data(xs_local[:,0], xs_local[:,1])
# compute and plot direction the robot is facing
a = xs_local[-1, 0]
b = xs_local[-1, 1]
a2 = a + np.cos(xs_local[-1, 2]) * 0.2
b2 = b + np.sin(xs_local[-1, 2]) * 0.2
self.dirs.set_data(np.array([a, a2]), np.array([b, b2]))
ol_x_local = deepcopy(self.ol_x)
ol_y_local = deepcopy(self.ol_y)
if ol_x_local is not None:
self.line_ol.set_data(ol_x_local, ol_y_local)
else:
self.line_ol.set_data([],[])
finally:
self.mutex.release()
return self.line, self.line_sim, self.dirm, self.dirs, self.line_ol, self.track_line_inner, self.track_line_outer,\
self.line_x, self.line_y,
def measurement_callback(self, data):
#print(data)
# detect robots
if data.id in self.robot_ids:
r = self.robot_ids[data.id]
r.pos = (data.x, data.y) # only x and y component are important for us
r.euler = data.angle
# save measured position and angle for plotting
measurement = np.array([r.pos[0], r.pos[1], r.euler])
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if r.tms_0 is None:
r.tms_0 = time.time()
r.xm_0 = measurement
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self.mutex.acquire()
try:
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r.tms = np.array([0.0])
r.xms = measurement
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finally:
self.mutex.release()
else:
self.mutex.acquire()
try:
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r.tms = np.vstack((r.tms, time.time() - r.tms_0))
r.xms = np.vstack((r.xms, measurement))
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finally:
self.mutex.release()
def controller(self):
print("starting control")
running = True
while running:
(clientsocket, address) = self.comm_socket.accept()
clientsocket.settimeout(None)
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connected = True
while connected:
try:
data = myreceive(clientsocket)
print(data)
inputs = data.split(b',')
cmd = inputs[0]
cmd = cmd.strip()
if len(inputs) > 1:
if cmd in self.valid_cmds:
try:
robot_id = int(inputs[1])
except ValueError:
print("could not read robot id!")
clientsocket.sendall(b'Could not read robot id!\n')
if robot_id in self.robot_ids:
if cmd == 'get position':
clientsocket.sendall(bytes('{}\n'.format(self.robot_ids[robot_id].grid_pos)))
elif cmd == 'set position':
try:
pos_data = ",".join(inputs[2:])
new_grid_pos = tuple(map(lambda x: int(x[1]) if x[0] < 2 else float(x[1]), enumerate(pos_data.strip().strip('()').split(','))))
self.robot_ids[robot_id].grid_pos = new_grid_pos
except IndexError as e:
print("could not set grid position!")
clientsocket.sendall(bytes(
'could not set grid position! (invalid format)\n'.format(
self.robot_ids[robot_id].grid_pos)))
except ValueError as e:
print("could not set grid position!")
clientsocket.sendall(bytes('could not set grid position! (invalid format)\n'.format(self.robot_ids[robot_id].grid_pos)))
else:
self.mpc_control(robot_id, cmd)
clientsocket.sendall(b'OK\n')
else:
print("invalid robot id!")
clientsocket.sendall(b'Invalid robot id!\n')
else:
clientsocket.sendall(b'Invalid command!\n')
else: # len(inputs) <= 1
if 'quit' in inputs[0]:
clientsocket.close()
self.comm_socket.close()
connected = False
running = False
else:
print("could not process command!")
clientsocket.sendall(b'Could not process request!\n')
except RuntimeError:
print("disconnected")
connected = False
clientsocket.close()
def mpc_control(self, robot_id, cmd):
robot = self.robot_ids[robot_id] # get robot to be controlled
grid_pos = robot.grid_pos # grid position of the robot
# compute new grid position and orientation
if cmd == 'forward':
new_x = int(grid_pos[0] + 1 * np.cos(grid_pos[2]))
new_y = int(grid_pos[1] + 1 * np.sin(grid_pos[2]))
new_angle = grid_pos[2]
elif cmd == 'backward':
new_x = int(grid_pos[0] - 1 * np.cos(grid_pos[2]))
new_y = int(grid_pos[1] - 1 * np.sin(grid_pos[2]))
new_angle = grid_pos[2]
elif cmd == 'turn left':
new_x = grid_pos[0]
new_y = grid_pos[1]
new_angle = np.unwrap([0, grid_pos[2] + np.pi / 2])[1]
elif cmd == 'turn right':
new_x = grid_pos[0]
new_y = grid_pos[1]
new_angle = np.unwrap([0, grid_pos[2] - np.pi / 2])[1]
elif cmd == 'turn around':
new_x = grid_pos[0]
new_y = grid_pos[1]
new_angle = np.unwrap([0, grid_pos[2] + np.pi])[1]
else:
print("unknown command!")
sys.exit(1)
grid_pos = (new_x, new_y, new_angle)
print("new grid pos for robot {}: {}".format(robot_id, grid_pos))
self.target = np.array((0.25 * grid_pos[0], 0.25 * grid_pos[1], grid_pos[2]))
self.pid = False
self.mpc = True
near_target = 0
while near_target < 5:
# open loop controller
events = pygame.event.get()
for event in events:
if event.type == pygame.KEYDOWN:
if event.key == pygame.K_UP:
self.controlling = True
self.t = time.time()
elif event.key == pygame.K_DOWN:
self.controlling = False
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if self.robot_ids[robot_id].socket:
self.robot_ids[robot_id].socket.send('(0.0,0.0)\n')
elif event.key == pygame.K_0:
self.target = np.array([0,0,0])
elif event.key == pygame.K_PLUS:
self.control_scaling += 0.1
self.control_scaling = min(self.control_scaling, 1.0)
print("control scaling = ", self.control_scaling)
elif event.key == pygame.K_MINUS:
self.control_scaling -= 0.1
self.control_scaling = max(self.control_scaling, 0.1)
print("control scaling = ", self.control_scaling)
elif event.key == pygame.K_ESCAPE:
print("quit!")
self.controlling = False
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if self.robot_ids[robot_id].socket:
self.robot_ids[robot_id].socket.send('(0.0,0.0)\n')
self.anim_stopped = True
return
elif event.key == pygame.QUIT:
print("quit!")
self.controlling = False
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if self.robot_ids[robot_id].socket:
self.robot_ids[robot_id].socket.send('(0.0,0.0)\n')
self.anim_stopped = True
return
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if self.mpc:
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x_pred = self.get_measurement_prediction(robot_id)
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tmpc_start = time.time()
error_pos = np.linalg.norm(x_pred[0:2] - self.target[0:2])
angles_unwrapped = np.unwrap([x_pred[2], self.target[2]]) # unwrap angle to avoid jump in data
error_ang = np.abs(angles_unwrapped[0] - angles_unwrapped[1])
#print("error pos = ", error_pos)
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print("error_pos = {}, error_ang = {}".format(error_pos, error_ang))
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if error_pos > 0.075 or error_ang > 0.35:
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# solve mpc open loop problem
res = self.ols.solve(x_pred, self.target)
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#us1 = res[0]
#us2 = res[1]
us1 = res[0] * self.control_scaling
us2 = res[1] * self.control_scaling
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#print("u = {}", (us1, us2))
# save open loop trajectories for plotting
self.mutex.acquire()
try:
self.ol_x = res[2]
self.ol_y = res[3]
finally:
self.mutex.release()
tmpc_end = time.time()
#print("---------------- mpc solution took {} seconds".format(tmpc_end - tmpc_start))
dt_mpc = time.time() - self.t
if dt_mpc < self.dt: # wait until next control can be applied
#print("sleeping for {} seconds...".format(self.dt - dt_mpc))
time.sleep(self.dt - dt_mpc)
else:
us1 = [0] * self.mstep
us2 = [0] * self.mstep
near_target += 1
robot.grid_pos = grid_pos
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# send controls to the robot
for i in range(0, self.mstep): # option to use multistep mpc if len(range) > 1
u1 = us1[i]
u2 = us2[i]
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if self.robot_ids[robot_id].socket:
self.robot_ids[robot_id].socket.send('({},{})\n'.format(u1, u2))
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if i < self.mstep:
time.sleep(self.dt)
self.t = time.time() # save time the most recent control was applied
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def get_measurement_prediction(self, robot_id):
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# get measurement
self.mutex.acquire()
try:
window = 3
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last_measurement = copy.deepcopy(self.robot_ids[robot_id].xms[-window:])
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#print("last_measurements = {}".format(last_measurement))
#print("mean = {}".format(np.mean(last_measurement, axis=0)))
last_measurement = np.mean(last_measurement, axis=0)
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last_time = copy.deepcopy(self.robot_ids[robot_id].tms[-1])
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finally:
self.mutex.release()
# prediction of state at time the mpc will terminate
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self.r.set_f_params(np.array([self.robot_ids[robot_id].u1 * self.omega_max, self.robot_ids[robot_id].u2 * self.omega_max]))
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self.r.set_initial_value(last_measurement, last_time)
x_pred = self.r.integrate(self.r.t + self.dt)
return x_pred
def get_measurement(self):
self.mutex.acquire()
try:
last_measurement = copy.deepcopy(self.xms[-1:])
finally:
self.mutex.release()
return last_measurement[0]
def pos_getter(self):
while True:
x_pred = self.get_measurement_prediction()
print("pos = ", x_pred)
def main(args):
parser = ArgumentParser()
parser.add_argument('id', metavar='id', type=str, help='marker id of the controlled robot')
parser.add_argument('ip', metavar='ip', type=str, help='ip address of the controlled robot')
args = parser.parse_args()
marker_id = int(args.id)
ip = args.ip
rospy.init_node('controller_node', anonymous=True)
rc = RemoteController(marker_id, ip)
pygame.init()
screenheight = 480
screenwidth = 640
pygame.display.set_mode([screenwidth, screenheight])
# print("waiting until track is completely detected")
# while not rc.track.track_complete:
# pass
#threading.Thread(target=rc.input_handling).start()
controller_thread = threading.Thread(target=rc.controller)
controller_thread.start()
#time.sleep(10)
#rc.ani()
if __name__ == '__main__':
main(sys.argv)