# 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 import time from casadi_opt import OpenLoopSolver from marker_pos_angle.msg import id_pos_angle class Robot: def __init__(self, id, ip=None): self.pos = None self.orient = None self.id = id self.pos = None self.euler = None self.ip = ip class Obstacle: def __init__(self, id, radius): self.id = id self.pos = None self.radius = radius 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): self.robots = [Robot(3, '192.168.1.103')] self.robot_ids = {} for r in self.robots: self.robot_ids[r.id] = r obst = [Obstacle(6, 0.175), Obstacle(5, 0.175), Obstacle(8, 0.175)] self.obstacles = {} for r in obst: self.obstacles[r.id] = r # connect to robot self.rc_socket = socket.socket() #self.rc_socket = None try: for r in self.robots: self.rc_socket.connect((r.ip, 1234)) # connect to robot except socket.error: print("could not connect to socket") self.rc_socket = None self.t = time.time() # variables for simulated state self.x0 = None self.ts = np.array([]) self.xs = [] # variables for measurements self.tms_0 = None self.xm_0 = None self.tms = None self.xms = None # 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 # currently active control self.u1 = 0.0 self.u2 = 0.0 # animation self.fig = plt.figure() self.ax = self.fig.add_subplot(1,1,1) 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.circles = [] for o in self.obstacles: self.circles.append(patch.Circle((0.0, 0.0), radius=0.1, fill=False, color='red', linestyle='--')) for s in self.circles: self.ax.add_artist(s) plt.xlabel('x-position') plt.ylabel('y-position') plt.grid() self.ols = OpenLoopSolver() 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 def ani(self): 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') return self.line, self.line_sim, self.dirm, self.dirs, self.line_ol, self.circles[0], self.circles[1],self.circles[2], def ani_update(self, frame): #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])) 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([],[]) i = 0 obst_keys = self.obstacles.keys() for s in self.circles: o = self.obstacles[obst_keys[i]] i = i + 1 if o.pos is not None: s.center = o.pos s.radius = o.radius finally: self.mutex.release() return self.line, self.line_sim, self.dirm, self.dirs, self.line_ol, self.circles[0], self.circles[1],self.circles[2], def measurement_callback(self, 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]) if self.tms_0 is None: self.tms_0 = time.time() self.xm_0 = measurement self.mutex.acquire() try: self.tms = np.array([0.0]) self.xms = measurement finally: self.mutex.release() else: self.mutex.acquire() try: self.tms = np.vstack((self.tms, time.time() - self.tms_0)) self.xms = np.vstack((self.xms, measurement)) finally: self.mutex.release() # detect obstacles if data.id in self.obstacles.keys(): obst = (data.x, data.y) self.obstacles[data.id].pos = obst def controller(self): print("starting control") while True: # 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 if self.rc_socket: self.rc_socket.send('(0.0,0.0)\n') elif event.key == pygame.K_0: self.target = (0.0, 0.0, 0.0) elif event.key == pygame.K_1: self.target = (0.5,0.5, -np.pi/2.0) elif event.key == pygame.K_2: self.target = (0.5, -0.5, 0.0) elif event.key == pygame.K_3: self.target = (-0.5,-0.5, np.pi/2.0) elif event.key == pygame.K_4: self.target = (-0.5,0.5, 0.0) if self.controlling: x_pred = self.get_measurement_prediction() tmpc_start = time.time() # solve mpc open loop problem res = self.ols.solve(x_pred, self.target, self.obstacles) us1 = res[0] us2 = res[1] # 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) # send controls to the robot for i in range(0, 1): # option to use multistep mpc if len(range) > 1 u1 = us1[i] u2 = us2[i] if self.rc_socket: self.rc_socket.send('({},{})\n'.format(u1, u2)) self.t = time.time() # save time the most recent control was applied def get_measurement_prediction(self): # get measurement self.mutex.acquire() try: last_measurement = copy.deepcopy(self.xms[-1]) last_time = copy.deepcopy(self.tms[-1]) finally: self.mutex.release() # prediction of state at time the mpc will terminate self.r.set_f_params(np.array([self.u1 * self.omega_max, self.u2 * self.omega_max])) self.r.set_initial_value(last_measurement, last_time) x_pred = self.r.integrate(self.r.t + self.dt) return x_pred def main(args): rospy.init_node('controller_node', anonymous=True) rc = RemoteController() pygame.init() screenheight = 480 screenwidth = 640 pygame.display.set_mode([screenwidth, screenheight]) #threading.Thread(target=rc.input_handling).start() threading.Thread(target=rc.controller).start() rc.ani() if __name__ == '__main__': main(sys.argv)