RoboRally/remote_control/position_controller.py

# 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, 0.2), Obstacle(5, 0.2), Obstacle(8, 0.2)]

        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()

        marker_sub = rospy.Subscriber("/marker_id_pos_angle", id_pos_angle, self.measurement_callback)


        # pid parameters
        self.k = 0
        self.ii = 0.1
        self.pp = 0.4

        self.inc = 0.0

        self.alphas = []

        self.speed = 1.0
        self.controlling = False

        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.target = (0.0, 0.0, 0.0)

    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):
        #print("data = {}".format(data))
        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

            #print("r.pos = {}".format(r.pos))
            #print("r.angle = {}".format(r.euler))

            # 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()

        if data.id in self.obstacles.keys():
            obst = (data.x, data.y)
            self.obstacles[data.id].pos = obst

    def controller(self):
        tgrid = None
        us1 = None
        us2 = None
        u1 = -0.0
        u2 = 0.0

        r = scipy.integrate.ode(f_ode)

        omega_max = 5.0

        init_pos = None
        init_time = None
        final_pos = None
        final_time = None
        forward = True
        print("starting control")
        while True:

            keyboard_control = False
            keyboard_control_speed_test = False
            pid = False
            open_loop_solve = True

            if keyboard_control: # keyboard controller
                events = pygame.event.get()
                speed = 1.0
                for event in events:
                    if event.type == pygame.KEYDOWN:
                        if event.key == pygame.K_LEFT:
                            self.u1 = -speed
                            self.u2 = speed
                            #print("turn left: ({},{})".format(u1, u2))
                        elif event.key == pygame.K_RIGHT:
                            self.u1 = speed
                            self.u2 = -speed
                            #print("turn right: ({},{})".format(u1, u2))
                        elif event.key == pygame.K_UP:
                            self.u1 = speed
                            self.u2 = speed
                            #print("forward: ({},{})".format(self.u1, self.u2))
                        elif event.key == pygame.K_DOWN:
                            self.u1 = -speed
                            self.u2 = -speed
                            #print("forward: ({},{})".format(u1, u2))
                        self.rc_socket.send('({},{},{})\n'.format(0.1, self.u1, self.u2))
                    elif event.type == pygame.KEYUP:
                        self.u1 = 0
                        self.u2 = 0
                        #print("key released, resetting: ({},{})".format(u1, u2))
                        self.rc_socket.send('({}, {},{})\n'.format(0.1, self.u1, self.u2))

                tnew = time.time()
                dt = tnew - self.t
                r = scipy.integrate.ode(f_ode)
                r.set_f_params(np.array([self.u1 * omega_max, self.u2 * omega_max]))

                #print(self.x0)
                if self.x0 is None:
                    if self.xm_0 is not None:
                        self.x0 = self.xm_0
                        self.xs = self.x0
                    else:
                        print("error: no measurement available to initialize simulation")
                x = self.x0
                r.set_initial_value(x, self.t)
                xnew = r.integrate(r.t + dt)

                self.t = tnew
                self.x0 = xnew

                self.mutex.acquire()
                try:
                    self.ts = np.append(self.ts, tnew)
                    self.xs = np.vstack((self.xs, xnew))
                finally:
                    self.mutex.release()


            elif keyboard_control_speed_test:
                events = pygame.event.get()
                for event in events:
                    if event.type == pygame.KEYDOWN:
                        if event.key == pygame.K_1:
                            self.controlling = True
                            forward = True
                            print("starting test")
                            self.mutex.acquire()
                            try:
                                init_pos = copy.deepcopy(self.xms[-1])
                                init_time = copy.deepcopy(self.tms[-1])
                            finally:
                                self.mutex.release()
                        if event.key == pygame.K_2:
                            self.controlling = True
                            forward = False
                            print("starting test")
                            self.mutex.acquire()
                            try:
                                init_pos = copy.deepcopy(self.xms[-1])
                                init_time = copy.deepcopy(self.tms[-1])
                            finally:
                                self.mutex.release()
                        elif event.key == pygame.K_3:
                            self.controlling = False
                            print("stopping test")
                            self.rc_socket.send('(0.1, 0.0,0.0)\n')

                            self.mutex.acquire()
                            try:
                                final_pos = copy.deepcopy(self.xms[-1])
                                final_time = copy.deepcopy(self.tms[-1])
                            finally:
                                self.mutex.release()

                            print("init_pos = {}".format(init_pos))
                            print("final_pos = {}".format(final_pos))
                            print("distance = {}".format(np.linalg.norm(init_pos[0:2]-final_pos[0:2])))
                            print("dt = {}".format(final_time - init_time))

                            d = np.linalg.norm(init_pos[0:2]-final_pos[0:2])
                            t = final_time - init_time
                            r = 0.03

                            angular_velocity = d/r/t
                            print("average angular velocity = {}".format(angular_velocity))


                if self.controlling:
                    if forward:
                        self.rc_socket.send('(0.1, 1.0,1.0)\n')
                    else:
                        self.rc_socket.send('(0.1, -1.0,-1.0)\n')
                    time.sleep(0.1)
                    #print("speed = {}".format(self.speed))


            elif open_loop_solve:
                # 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:
                    # get measurement
                    self.mutex.acquire()
                    try:
                        last_measurement = copy.deepcopy(self.xms[-1])
                        last_time = copy.deepcopy(self.tms[-1])
                    finally:
                        self.mutex.release()

                    #print("current measurement (t, x) = ({}, {})".format(last_time, last_measurement))
                    #print("current control (u1, u2) = ({}, {})".format(u1, u2))

                    # prediction of state at time the mpc will terminate
                    r.set_f_params(np.array([u1 * omega_max, u2 * omega_max]))

                    r.set_initial_value(last_measurement, last_time)
                    dt = self.ols.T/self.ols.N
                    #print("integrating for {} seconds".format((dt)))
                    x_pred = r.integrate(r.t + (dt))

                    #print("predicted initial state x_pred = ({})".format(x_pred))

                    tmpc_start = time.time()

                    res = self.ols.solve(x_pred, self.target, self.obstacles)
                    #tgrid = res[0]
                    us1 = res[0]
                    us2 = res[1]

                    self.mutex.acquire()
                    try:
                        self.ol_x = res[2]
                        self.ol_y = res[3]
                    finally:
                        self.mutex.release()

                    # tt = 0
                    # x = last_measurement
                    # t_ol = np.array([tt])
                    # x_ol = np.array([x])
                    # # compute open loop prediction
                    # for i in range(len(us1)):
                    #     r = scipy.integrate.ode(f_ode)
                    #     r.set_f_params(np.array([us1[i] * 13.32, us2[i] * 13.32]))
                    #     r.set_initial_value(x, tt)
                    #
                    #     tt = tt + 0.1
                    #     x = r.integrate(tt)
                    #
                    #     t_ol = np.vstack((t_ol, tt))
                    #     x_ol = np.vstack((x_ol, x))

                    #plt.figure(4)
                    #plt.plot(x_ol[:,0], x_ol[:,1])


                #if event.key == pygame.K_DOWN:
                #    if tgrid is not None:
                    tmpc_end = time.time()
                    print("---------------- mpc solution took {} seconds".format(tmpc_end - tmpc_start))
                    dt_mpc = time.time() - self.t
                    if dt_mpc < dt:
                        print("sleeping for {} seconds...".format(dt - dt_mpc))
                        time.sleep(dt - dt_mpc)

                    self.mutex.acquire()
                    try:
                        second_measurement = copy.deepcopy(self.xms[-1])
                        second_time = copy.deepcopy(self.tms[-1])
                    finally:
                        self.mutex.release()

                    #print("(last_time, second_time, dt) = ({}, {}, {})".format(last_time, second_time, second_time - last_time))
                    #print("mismatch between predicted state and measured state: {}\n\n".format(second_measurement - last_measurement))

                    for i in range(0, 1):
                        u1 = us1[i]
                        u2 = us2[i]
                        #self.rc_socket.send('({},{},{})\n'.format(dt,u1, u2))
                        if self.rc_socket:
                            self.rc_socket.send('({},{})\n'.format(u1, u2))
                        self.t = time.time()
                        #time.sleep(0.2)
                    #


                    pass

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.controller).start()

    rc.ani()


if __name__ == '__main__':
    main(sys.argv)