enabled backwards driving and adjusted parameters a bit

micropython_firmware/d1motor.py

@@ -10,6 +10,10 @@ m0.speed(5000)
 
 """
 import ustruct
+import utime
+import math
+
+sign = lambda x: math.copysign(1, x)
 
 
 _STATE_BRAKE = const(0)
@@ -49,6 +53,10 @@ class Motor:
     def speed(self, speed=None):
         if speed is None:
             return self._speed
+        if abs(speed) < 30 and abs(speed) > 10: # kick-start for small speeds
+            self.speed(int(100 * sign(speed)))
+            utime.sleep_ms(5)
+
         if speed > 0:
             self._speed = min(10000, max(1, speed))
             self._state = _STATE_RIGHT

micropython_firmware/main.py

@@ -2,7 +2,7 @@ import machine
 import sys
 from machine import I2C, Pin
 
-i2c = True
+i2c = False
 if i2c:
     import d1motor
 else:
@@ -100,5 +100,5 @@ class Robot:
                 del comm_socket
                 del socket
 
-wall_e = Robot()
+wall_e = Robot(i2c=i2c)
 wall_e.remote_control()

remote_control/aruco_estimator.py

@@ -0,0 +1,400 @@
+import pyrealsense2 as rs
+import numpy as np
+import cv2
+import os
+import time
+
+from shapely.geometry import LineString
+from queue import Queue
+
+import aruco
+
+class ArucoEstimator:
+    corner_marker_ids = {
+        'a': 0,
+        'b': 1,
+        'c': 2,
+        'd': 3
+    }
+
+    corner_estimates = {
+        'a': {'pixel_coordinate': None, 'x': None, 'y': None, 'n_estimates': 0},
+        'b': {'pixel_coordinate': None, 'x': None, 'y': None, 'n_estimates': 0},
+        'c': {'pixel_coordinate': None, 'x': None, 'y': None, 'n_estimates': 0},
+        'd': {'pixel_coordinate': None, 'x': None, 'y': None, 'n_estimates': 0},
+    }
+
+    def __init__(self, robot_marker_ids=None, use_realsense=True, grid_columns=8, grid_rows=8):
+        self.grid_columns = grid_columns
+        self.grid_rows = grid_rows
+
+        if robot_marker_ids is None:
+            robot_marker_ids = []
+        self.robot_marker_ids = robot_marker_ids
+        self.robot_marker_estimates = dict([(marker_id, {'t': None, 'x': None, 'y': None, 'angle': None})
+                                            for marker_id in self.robot_marker_ids])
+
+        self.draw_grid = False
+
+        self.event_queue = Queue()
+
+        if use_realsense:  # check if realsense camera is connected
+            # Configure depth and color streams
+            self.pipeline = rs.pipeline()
+            config = rs.config()
+            #config.enable_stream(rs.stream.color, 1920, 1080, rs.format.bgr8, 30)
+            config.enable_stream(rs.stream.color, 1280, 720, rs.format.bgr8, 30)
+
+            # Start streaming
+            self.pipeline.start(config)
+
+            # disable auto exposure
+            color_sensor = self.pipeline.get_active_profile().get_device().query_sensors()[1]
+            color_sensor.set_option(rs.option.enable_auto_exposure, False)
+
+            camera_intrinsics = self.pipeline.get_active_profile().get_stream(
+                rs.stream.color).as_video_stream_profile().get_intrinsics()
+            self.camera_matrix = np.zeros((3, 3))
+            self.camera_matrix[0][0] = camera_intrinsics.fx
+            self.camera_matrix[1][1] = camera_intrinsics.fy
+            self.camera_matrix[0][2] = camera_intrinsics.ppx
+            self.camera_matrix[1][2] = camera_intrinsics.ppy
+            self.dist_coeffs = np.array(camera_intrinsics.coeffs)
+            # more info: https://dev.intelrealsense.com/docs/projection-in-intel-realsense-sdk-20
+        else:
+            # use other camera
+            self.cv_camera = cv2.VideoCapture(0)
+            self.pipeline = None
+
+        # create detector and get parameters
+        self.detector = aruco.MarkerDetector()
+        # self.detector.setDictionary('ARUCO_MIP_36h12')
+        #self.detector.setDictionary('ARUCO_MIP_16h3')
+        # self.detector.setDictionary('ARUCO')
+        #self.detector.setDetectionMode(aruco.DM_NORMAL, 0.05)
+        self.detector.setDetectionMode(aruco.DM_VIDEO_FAST, 0.05)
+
+        self.detector_params = self.detector.getParameters()
+
+        # print detector parameters
+        print("detector params:")
+        for val in dir(self.detector_params):
+            if not val.startswith("__"):
+                print("\t{} : {}".format(val, self.detector_params.__getattribute__(val)))
+
+        self.camparam = aruco.CameraParameters()
+        if use_realsense:
+            self.camparam.readFromXMLFile(os.path.join(os.path.dirname(__file__), "realsense.yml"))
+        else:
+            self.camparam.readFromXMLFile(os.path.join(os.path.dirname(__file__), "dfk72_6mm_param2.yml"))
+        print(self.camparam)
+
+    def mouse_callback(self, event, px, py, flags, param):
+        """
+        This function is called for each mouse event inside the opencv window.
+        If there are reference markers available we compute the real world position corresponding to the clicked
+        position and put it in an event queue.
+        :param event: type of event (mouse movement, left click, right click, etc.)
+        :param px: x-position of event
+        :param py: y-position of event
+        """
+        if event == cv2.EVENT_LBUTTONDOWN:
+            if self.all_corners_detected():
+                # inter/extrapolate from clicked point to marker position
+                px1 = self.corner_estimates['a']['pixel_coordinate'][0]
+                px3 = self.corner_estimates['c']['pixel_coordinate'][0]
+                py1 = self.corner_estimates['a']['pixel_coordinate'][1]
+                py3 = self.corner_estimates['c']['pixel_coordinate'][1]
+
+                x1 = self.corner_estimates['a']['x']
+                x3 = self.corner_estimates['c']['x']
+                y1 = self.corner_estimates['a']['y']
+                y3 = self.corner_estimates['c']['y']
+
+                alpha = (px - px1) / (px3 - px1)
+                beta = (py - py1) / (py3 - py1)
+
+                print(f"alpha = {alpha}, beta = {beta}")
+
+                target_x = x1 + alpha * (x3 - x1)
+                target_y = y1 + beta * (y3 - y1)
+                target = np.array([target_x, target_y, 0])
+
+                print(f"target = ({target_x},{target_y})")
+                self.event_queue.put(('click', target))
+            else:
+                print("not all markers have been detected!")
+
+    def run_tracking(self, draw_markers=True, draw_marker_coordinate_system=False, invert_grayscale=False):
+        """
+        Run the marker tracking in a loop
+        """
+        cv2.namedWindow('RoboRally', cv2.WINDOW_AUTOSIZE)
+        cv2.setMouseCallback('RoboRally', self.mouse_callback)
+
+        try:
+            running = True
+            while running:
+                if self.pipeline:
+                    frames = self.pipeline.wait_for_frames()
+                    color_frame = frames.get_color_frame()
+                    if not color_frame:
+                        continue
+                    # Convert images to numpy arrays
+                    color_image = np.asanyarray(color_frame.get_data())
+                else:
+                    # Capture frame-by-frame
+                    ret, color_image = self.cv_camera.read()
+                t_image = time.time()
+
+                gray = cv2.cvtColor(color_image, cv2.COLOR_BGR2GRAY)
+                if invert_grayscale:
+                    cv2.bitwise_not(gray, gray)
+
+                # run aruco marker detection
+                detected_markers = self.detector.detect(gray)
+
+                # extract data for detected markers
+                detected_marker_data = {}
+                for marker in detected_markers:
+                    detected_marker_data[marker.id] = {'marker_center': marker.getCenter()}
+                    if marker.id >= 0:
+                        if marker.id in self.corner_marker_ids.values():
+                            marker.calculateExtrinsics(0.1, self.camparam)
+                        else:
+                            marker.calculateExtrinsics(0.07, self.camparam)
+                        detected_marker_data[marker.id]['Rvec'] = marker.Rvec
+                        detected_marker_data[marker.id]['Tvec'] = marker.Tvec
+
+                    if marker.id >= 0:  # draw markers onto the image
+                        if draw_markers:
+                            marker.draw(color_image, np.array([255, 255, 255]), 2, True)
+
+                        if draw_marker_coordinate_system:
+                            aruco.CvDrawingUtils.draw3dAxis(color_image, self.camparam, marker.Rvec, marker.Tvec, .1)
+
+                # store data
+                for marker_id, data in detected_marker_data.items():
+                    self.update_estimate(marker_id, data['marker_center'], data['Rvec'], data['Tvec'], t_image)
+
+                # draw grid
+                if self.draw_grid:
+                    color_image = self.draw_grid_lines(color_image, detected_marker_data)
+                color_image = self.draw_robot_pos(color_image, detected_marker_data)
+
+                # Show images
+                cv2.imshow('RoboRally', color_image)
+                key = cv2.waitKey(1)
+
+                if key > 0:
+                    self.event_queue.put(('key', key))
+                    if key == ord('g'):
+                        self.draw_grid = not self.draw_grid
+                    if key == ord('q'):
+                        running = False
+                    if key == ord('a'):
+                        color_sensor = self.pipeline.get_active_profile().get_device().query_sensors()[1]
+                        if color_sensor.get_option(rs.option.enable_auto_exposure) == 1.0:
+                            color_sensor.set_option(rs.option.enable_auto_exposure, False)
+                            print("auto exposure OFF")
+                        else:
+                            color_sensor.set_option(rs.option.enable_auto_exposure, True)
+                            print("auto exposure ON")
+        finally:
+            cv2.destroyAllWindows()
+            if self.pipeline is not None:
+                # Stop streaming
+                self.pipeline.stop()
+
+    def update_estimate(self, marker_id, pixel_coord_center, rvec, tvec, t_image):
+        # update the marker estimate with new data
+        if marker_id in self.corner_marker_ids.values():
+            # for corner markers we compute the mean of all measurements s.t. the position stabilizes over time
+            # (we assume the markers do not move)
+
+            # get corresponding corner to the detected marker
+            corner = next(filter(lambda key: self.corner_marker_ids[key] == marker_id, self.corner_marker_ids.keys()))
+            old_estimate_x = self.corner_estimates[corner]['x']
+            old_estimate_y = self.corner_estimates[corner]['y']
+            n_estimates = self.corner_estimates[corner]['n_estimates']
+
+            x = tvec[0][0]
+            y = -tvec[1][0]  # flip y coordinate
+            if not any([old_estimate_x is None, old_estimate_y is None]):
+                new_estimate_x = (n_estimates * old_estimate_x + x) / (n_estimates + 1)  # weighted update
+                new_estimate_y = (n_estimates * old_estimate_y + y) / (n_estimates + 1)
+            else:
+                new_estimate_x = x  # first estimate
+                new_estimate_y = y
+            self.corner_estimates[corner]['t'] = t_image
+            self.corner_estimates[corner]['x'] = new_estimate_x
+            self.corner_estimates[corner]['y'] = new_estimate_y
+            self.corner_estimates[corner]['n_estimates'] = n_estimates + 1
+            self.corner_estimates[corner]['pixel_coordinate'] = pixel_coord_center
+
+        elif marker_id in self.robot_marker_ids:
+            # for robot markers we extract x and y position as well as the angle
+            # here we could also implement a filter
+            x = tvec[0][0]
+            y = -tvec[1][0]  # flip y coordinate
+
+            # compute angle
+            rot_mat, _ = cv2.Rodrigues(rvec)
+            pose_mat = cv2.hconcat((rot_mat, tvec))
+            _, _, _, _, _, _, euler_angles = cv2.decomposeProjectionMatrix(pose_mat)
+            angle = -euler_angles[2][0] * np.pi / 180.0
+
+            self.robot_marker_estimates[marker_id] = {'t': t_image, 'x': x, 'y': y, 'angle': angle}
+
+    def all_corners_detected(self):
+        # checks if all corner markers have been detected at least once
+        return not any([estimate['n_estimates'] == 0 for estimate in self.corner_estimates.values()])
+
+    def all_robots_detected(self):
+        # checks if all robot markers have been detected at least once
+        return not any([estimate['t'] is None for estimate in self.robot_marker_estimates.values()])
+
+    def get_pos_from_grid_point(self, x, y, orientation=None):
+        """
+         returns the position for the given grid point based on the current corner estimates
+        :param x: x position on the grid ( 0 &le x &lt number of grid columns)
+        :param y: y position on the grid ( 0 &le x &lt number of grid rows)
+        :param orientation: (optional) orientation in the given grid cell (one of ^, >, v, &lt )
+        :return: numpy array with corresponding real world x- and y-position
+                    if orientation was specified the array also contains the matching angle for the orientation
+        """
+        assert 0 <= x < self.grid_columns
+        assert 0 <= y < self.grid_rows
+        assert self.all_corners_detected()
+
+        # compute column line
+        a = np.array([self.corner_estimates['a']['x'], self.corner_estimates['a']['y']])
+        b = np.array([self.corner_estimates['b']['x'], self.corner_estimates['b']['y']])
+        c = np.array([self.corner_estimates['c']['x'], self.corner_estimates['c']['y']])
+        d = np.array([self.corner_estimates['d']['x'], self.corner_estimates['d']['y']])
+        x_frac = (x + 0.5) / self.grid_columns
+        y_frac = (y + 0.5) / self.grid_rows
+
+        vab = b - a
+        vdc = c - d
+        column_line_top = a + x_frac * vab
+        column_line_bottom = d + x_frac * vdc
+
+        vad = d - a
+        vbc = c - b
+        row_line_top = a + y_frac * vad
+        row_line_bottom = b + y_frac * vbc
+
+        column_line = LineString([column_line_top, column_line_bottom])
+        row_line = LineString([row_line_top, row_line_bottom])
+
+        int_pt = column_line.intersection(row_line)
+        point_of_intersection = np.array([int_pt.x, int_pt.y])
+
+        if orientation is not None:
+            # compute angle corresponding to the orientation w.r.t. the grid
+            # TODO: test this code
+            angle_ab = np.arctan2(vab[1], vab[0])
+            angle_dc = np.arctan2(vdc[1], vdc[0])
+
+            angle_ad = np.arctan2(vad[1], vad[0])
+            angle_bc = np.arctan2(vbc[1], vbc[0])
+
+            angle = 0.0
+            if orientation == '>':
+                angle = y_frac * angle_ab + (1 - y_frac) * angle_dc
+            elif orientation == '<':
+                angle = y_frac * angle_ab + (1 - y_frac) * angle_dc + np.pi
+            elif orientation == 'v':
+                angle = x_frac * angle_ad + (1 - x_frac) * angle_bc
+            elif orientation == '^':
+                angle = x_frac * angle_ad + (1 - x_frac) * angle_bc + np.pi
+
+            return np.array((point_of_intersection[0], point_of_intersection[1], angle))
+        else:
+            return point_of_intersection
+
+    def get_grid_point_from_pos(self):
+        # TODO return the nearest grid point for the given position estimate
+        pass
+
+    def print_corner_estimates(self):
+        for key, value in self.corner_estimates.items():
+            if value['n_estimates'] != 0:
+                print(f"corner marker {key} at pos ({value['x']},{value['y']})")
+
+    def draw_corner_line(self, frame, corner_1, corner_2):
+        # draws a line between the given markers onto the given frame
+        corner_1_center = self.corner_estimates[corner_1]['pixel_coordinate']
+        corner_2_center = self.corner_estimates[corner_2]['pixel_coordinate']
+        if corner_1_center is not None and corner_2_center is not None:
+            frame = cv2.line(frame, tuple(corner_1_center), tuple(corner_2_center), color=(0, 0, 255), thickness=2)
+        return frame
+
+    def draw_grid_lines(self, frame, detected_marker_data):
+        # draws a grid onto the given frame
+        frame = self.draw_corner_line(frame, 'a', 'b')
+        frame = self.draw_corner_line(frame, 'b', 'c')
+        frame = self.draw_corner_line(frame, 'c', 'd')
+        frame = self.draw_corner_line(frame, 'd', 'a')
+
+        if not any([estimate['pixel_coordinate'] is None for estimate in self.corner_estimates.values()]):
+            # compute outlines of board
+            a = self.corner_estimates['a']['pixel_coordinate']
+            b = self.corner_estimates['b']['pixel_coordinate']
+            c = self.corner_estimates['c']['pixel_coordinate']
+            d = self.corner_estimates['d']['pixel_coordinate']
+
+            # draw vertical lines
+            vab = b - a
+            vdc = c - d
+            for x in range(1, self.grid_columns):
+                column_line_top = a + x / self.grid_columns * vab
+                column_line_bottom = d + x / self.grid_columns * vdc
+                frame = cv2.line(frame, tuple(column_line_top), tuple(column_line_bottom), color=(0, 255, 0),
+                                 thickness=1)
+
+            # draw horizontal lines
+            vad = d - a
+            vbc = c - b
+            for y in range(1, self.grid_rows):
+                row_line_top = a + y / self.grid_rows * vad
+                row_line_bottom = b + y / self.grid_rows * vbc
+                frame = cv2.line(frame, tuple(row_line_top), tuple(row_line_bottom), color=(0, 255, 0),
+                                 thickness=1)
+
+        return frame
+
+    def get_robot_state_estimate(self, marker_id):
+        if marker_id in self.robot_marker_estimates:
+            if self.robot_marker_estimates[marker_id]['t'] is not None:
+                return np.array([self.robot_marker_estimates[marker_id]['x'],
+                                 self.robot_marker_estimates[marker_id]['y'],
+                                 self.robot_marker_estimates[marker_id]['angle']])
+            else:
+                print(f"error: no estimate available for robot {marker_id}")
+                return None
+        else:
+            print(f"error: invalid robot id {marker_id}")
+            return None
+
+    def draw_robot_pos(self, frame, detected_marker_data):
+        # draws information about the robot positions onto the given frame
+        robot_corners_pixel_coords = {}
+        for marker_id, estimate in self.robot_marker_estimates.items():
+            if marker_id in detected_marker_data.keys():
+                robot_corners_pixel_coords[marker_id] = tuple(detected_marker_data[marker_id]['marker_center'])
+
+        for marker_id, coord in robot_corners_pixel_coords.items():
+            x = self.robot_marker_estimates[marker_id]['x']
+            y = self.robot_marker_estimates[marker_id]['y']
+            angle = self.robot_marker_estimates[marker_id]['angle']
+            #frame = cv2.putText(frame, "pos = ({:5.3f}, {:5.3f}), ang = {:5.3f}".format(x, y, angle), coord,
+            #                    cv2.FONT_HERSHEY_SIMPLEX, 0.50, (0, 255, 0))
+            frame = cv2.putText(frame, f"{marker_id}", coord, cv2.FONT_HERSHEY_PLAIN, 2, (0, 255, 255), thickness=4)
+        return frame
+
+
+if __name__ == "__main__":
+    estimator = ArucoEstimator(use_realsense=True, robot_marker_ids=[11, 12, 13, 14])
+    estimator.run_tracking(draw_markers=True, invert_grayscale=True)

remote_control/casadi_opt.py

@@ -3,6 +3,9 @@ import time
 
 # look at: https://github.com/casadi/casadi/blob/master/docs/examples/python/vdp_indirect_multiple_shooting.py
 
+# TODO for roborally
+# implement essential movements: forward, backward, turn left, turn right on grid-based level
+
 class OpenLoopSolver:
     def __init__(self, N=20, T=4.0):
         self.T = T
@@ -40,7 +43,8 @@ class OpenLoopSolver:
 
         # cost functional
         target = (-0.0, 0.0)
-        L = (x-target[0]) ** 2 + (y-target[1]) ** 2 + 1e-2 * theta ** 2 + 1e-2 * (omegar ** 2 + omegal ** 2)
+        L = (x-target[0]) ** 2 + (y-target[1]) ** 2 + 1e-2 * (omegar ** 2 + omegal ** 2)
+        #L = (x-target[0]) ** 2 + (y-target[1]) ** 2 + 1e-2 * theta ** 2 + 1e-2 * (omegar ** 2 + omegal ** 2)
 
         # Fixed step Runge-Kutta 4 integrator
         M = 4  # RK4 steps per interval
@@ -138,7 +142,12 @@ class OpenLoopSolver:
         #return
 
 
-    def solve(self, x0, target, obstacles, track):
+    def solve(self, x0, target):
+
+        angles_unwrapped = np.unwrap([x0[2], target[2]])  # unwrap angle to avoid jump in data
+        x0[2] = angles_unwrapped[0]
+        target[2] = angles_unwrapped[1]
+
         tstart = time.time()
         # alternative solution using multiple shooting (way faster!)
         self.opti = Opti() # Optimization problem
@@ -186,7 +195,11 @@ class OpenLoopSolver:
             theta)) * omegal * omega_max
         f3 = -(r / (2 * R) * omegar - r / (2 * R) * omegal) * omega_max
         xdot = vertcat(f1, f2, f3)
-        L = (x - target[0]) ** 2 + (y - target[1]) ** 2 + 1e-2 * (theta - target[2]) ** 2 + 1e-2 * (omegar ** 2 + omegal ** 2)
+
+        #L = 100 * (x - target[0]) ** 2 + 100 * (y - target[1]) ** 2  + 1e-1 * (theta - target[2])**2 + 1e-2 * (omegar ** 2 + omegal ** 2)
+        L = 100 * (x - target[0]) ** 2 + 100 * (y - target[1]) ** 2 + 1e-1 * (target[2] - theta) ** 2 + 1e-2 * (
+                    omegar ** 2 + omegal ** 2)
+        #L = (x - target[0]) ** 2 + (y - target[1]) ** 2 + 1e-2 * (theta - target[2]) ** 2 + 1e-2 * (omegar ** 2 + omegal ** 2)
         self.f = Function('f', [state, control], [xdot, L])
         # ---- solve NLP              ------
 
@@ -222,31 +235,13 @@ class OpenLoopSolver:
         self.opti.subject_to(self.Q[:, 0] == 0.0)
 
 
-        solver = self.opti.solver("ipopt", {}, {"print_level": 0})
+        solver = self.opti.solver("ipopt", {'print_time': False}, {"print_level": 0})
 
         # ---- misc. constraints  ----------
         # self.opti.subject_to(X[1,:]>=0) # Time must be positive
         # self.opti.subject_to(X[2,:]<=4) # Time must be positive
         # self.opti.subject_to(X[2,:]>=-2) # Time must be positive
 
-        # avoid obstacle
-        for o in obstacles:
-            p = obstacles[o].pos
-            r = obstacles[o].radius
-            if p is not None:
-                for k in range(1,self.N):
-                    self.opti.subject_to((self.X[0,k]-p[0])**2 + (self.X[1,k]-p[1])**2 + self.slack > r**2)
-        # keep inside track
-        # TODO
-        # track_ids = track.inner.keys()
-        # a = track.outer[track_ids[0]]
-        # b = track.outer[track_ids[1]]
-        # c = track.outer[track_ids[2]]
-        # d = track.outer[track_ids[3]]
-        #
-        # for k in range(1, self.N):
-        #     self.opti.subject_to(self.opti.subject_to(self.X))
-
         posx = self.X[0, :]
         posy = self.X[1, :]
         angle = self.X[2, :]
@@ -256,7 +251,7 @@ class OpenLoopSolver:
         self.opti.subject_to(angle[0] == x0[2])  # finish line at position 1
         tend = time.time()
 
-        print("setting up  problem took {} seconds".format(tend - tstart))
+        #print("setting up  problem took {} seconds".format(tend - tstart))
 
         tstart = time.time()
         if self.use_warmstart and self.opti_x0 is not None:
@@ -267,7 +262,7 @@ class OpenLoopSolver:
                 print("could not set warmstart")
         sol = self.opti.solve()   # actual solve
         tend = time.time()
-        print("solving the problem took {} seconds".format(tend - tstart))
+        #print("solving the problem took {} seconds".format(tend - tstart))
 
         tstart = time.time()
         self.opti_x0 = sol.value(self.opti.x)
@@ -278,7 +273,7 @@ class OpenLoopSolver:
         u_opt_1 = sol.value(self.U[0,:])
         u_opt_2 = sol.value(self.U[1,:])
         tend = time.time()
-        print("postprocessing took {} seconds".format(tend - tstart))
+        #print("postprocessing took {} seconds".format(tend - tstart))
 
         return (u_opt_1, u_opt_2, sol.value(posx), sol.value(posy))
 

remote_control/keyboard_controller.py

@@ -28,27 +28,27 @@ while running:
             if event.key == pygame.K_LEFT:
                 u1 = -vmax 
                 u2 = vmax
-                print("turn left: ({},{})".format(u1, u2))
+                print(f"turn left: ({u1},{u2})")
             elif event.key == pygame.K_RIGHT:
                 u1 = vmax
                 u2 = -vmax
-                print("turn right: ({},{})".format(u1, u2))
+                print(f"turn right: ({u1},{u2})")
             elif event.key == pygame.K_UP:
                 u1 = vmax
                 u2 = vmax
-                print("forward: ({},{})".format(u1, u2))
+                print(f"forward: ({u1},{u2})")
             elif event.key == pygame.K_DOWN:
                 u1 = -vmax 
                 u2 = -vmax 
-                print("backward: ({},{})".format(u1, u2))
+                print(f"backward: ({u1},{u2})")
             elif event.key == pygame.K_ESCAPE:
                 print("quit")
                 running = False
                 u1 = 0.0
                 u2 = 0.0
-            rc_socket.send('({},{})\n'.format(u1, u2))
+            rc_socket.send(f'({u1},{u2})\n'.encode())
         elif event.type == pygame.KEYUP:
             print("key released, resetting: ({},{})".format(u1, u2))
-            rc_socket.send('({},{})\n'.format(u1, u2))
+            rc_socket.send(f'({u1},{u2})\n'.encode())
 
   

remote_control/measurement_client.py

@@ -0,0 +1,13 @@
+import socket
+
+HOST, PORT = "localhost", 42424
+
+robot_id = 15
+
+# SOCK_DGRAM is the socket type to use for UDP sockets
+sock = socket.socket(socket.AF_INET, socket.SOCK_DGRAM)
+
+sock.sendto(f"{robot_id}\n".encode(), (HOST, PORT))
+while True:
+    received = str(sock.recv(1024), "utf-8")
+    print("Received: {}".format(received))

remote_control/measurement_server.py

@@ -0,0 +1,46 @@
+import socketserver
+import threading
+import time
+
+from aruco_estimator import ArucoEstimator
+
+
+class MeasurementHandler(socketserver.BaseRequestHandler):
+    def handle(self) -> None:
+        data = self.request[0]
+        socket = self.request[1]
+        cur_thread = threading.current_thread()
+        print(f"current thread {cur_thread}")
+        try:
+            marker_id = int(data)
+            if marker_id in self.server.estimator.robot_marker_estimates:
+                while True:
+                    socket.sendto(f"{self.server.estimator.robot_marker_estimates[marker_id]}\n".encode(),
+                                  self.client_address)
+                    time.sleep(1.0 / self.server.max_measurements_per_second)
+            else:
+                socket.sendto("error: unknown robot marker id\n".encode(),
+                              self.client_address)
+        except ValueError:
+            socket.sendto("error: data not understood. expected robot marker id (int)\n".encode(), self.client_address)
+
+        return
+
+
+class MeasurementServer(socketserver.ThreadingMixIn, socketserver.UDPServer):
+    def __init__(self, server_address, RequestHandlerClass, estimator, max_measurements_per_second=30):
+        super().__init__(server_address, RequestHandlerClass)
+        self.estimator = estimator
+        self.max_measurements_per_second = max_measurements_per_second
+
+
+if __name__ == "__main__":
+    aruco_estimator = ArucoEstimator(use_realsense=False, robot_marker_ids=[15])
+    estimator_thread = threading.Thread(target=aruco_estimator.run_tracking)
+    estimator_thread.start()
+
+    with MeasurementServer(('127.0.0.1', 42424), MeasurementHandler, aruco_estimator,
+                           max_measurements_per_second=30) as measurement_server:
+        measurement_server.serve_forever()
+
+    # receive with: nc 127.0.0.1 42424 -u  -> 15 + Enter

remote_control/mpc_controller.py

@@ -0,0 +1,175 @@
+import numpy as np
+import time
+
+from casadi_opt import OpenLoopSolver
+
+
+class MPCController:
+    def __init__(self, estimator):
+        self.t = time.time()
+
+        self.estimator = estimator
+        self.controlling = False
+
+        self.mstep = 2
+        self.ols = OpenLoopSolver(N=20, T=1.0)
+        self.ols.setup()
+        self.dt = self.ols.T / self.ols.N
+
+        # integrator
+        self.omega_max = 5.0
+        self.control_scaling = 0.4
+
+    def move_to_pos(self, target_pos, robot, near_target_counter=5):
+        near_target = 0
+        while near_target < near_target_counter:
+            while not self.estimator.event_queue.empty():
+                event = self.estimator.event_queue.get()
+                print("event: ", event)
+                if event[0] == 'click':
+                    pass
+                elif event[0] == 'key':
+                    key = event[1]
+
+                    if key == 84:  # arrow up
+                        self.controlling = True
+                        self.t = time.time()
+                    elif key == 82:  # arrow down
+                        self.controlling = False
+                        robot.send_cmd()
+                    elif key == 48:  # 0
+                        target_pos = np.array([0.0, 0.0, 0.0])
+                    elif key == 43:  # +
+                        self.control_scaling += 0.1
+                        self.control_scaling = min(self.control_scaling, 1.0)
+                        print("control scaling = ", self.control_scaling)
+                    elif key == 45:  # -
+                        self.control_scaling -= 0.1
+                        self.control_scaling = max(self.control_scaling, 0.1)
+                        print("control scaling = ", self.control_scaling)
+                    elif key == 113:
+                        print("quit!")
+                        self.controlling = False
+                        robot.send_cmd()
+                        return
+                    elif key == 27:  # escape
+                        print("quit!")
+                        self.controlling = False
+                        robot.send_cmd()
+                        return
+
+            x_pred = self.get_measurement(robot.id)
+
+            if x_pred is not None:
+                error_pos = np.linalg.norm(x_pred[0:2] - target_pos[0:2])
+                angles_unwrapped = np.unwrap([x_pred[2], target_pos[2]])  # unwrap angle to avoid jump in data
+                error_ang = np.abs(angles_unwrapped[0] - angles_unwrapped[1])
+                # print("error pos = ", error_pos)
+                # print("error_pos = {}, error_ang = {}".format(error_pos, error_ang))
+
+                # if error_pos > 0.075 or error_ang > 0.35:
+                if error_pos > 0.05 or error_ang > 0.1:
+                    # solve mpc open loop problem
+                    res = self.ols.solve(x_pred, target_pos)
+
+                    # us1 = res[0]
+                    # us2 = res[1]
+                    us1 = res[0] * self.control_scaling
+                    us2 = res[1] * self.control_scaling
+                    # print("u = {}", (us1, us2))
+
+                    # 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
+
+                # 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]
+                    robot.send_cmd(u1, u2)
+                    if i < self.mstep:
+                        time.sleep(self.dt)
+                    self.t = time.time()  # save time the most recent control was applied
+            else:
+                print("robot not detected yet!")
+
+    def interactive_control(self, robots):
+        controlled_robot_number = 0
+        robot = robots[controlled_robot_number]
+
+        target_pos = np.array([0.0, 0.0, 0.0])
+
+        running = True
+        while running:
+            # handle events from opencv window
+            while not self.estimator.event_queue.empty():
+                event = self.estimator.event_queue.get()
+                print("event: ", event)
+                if event[0] == 'click':
+                    target_pos = event[1]
+                elif event[0] == 'key':
+                    key = event[1]
+
+                    if key == 32:  # arrow up
+                        self.controlling = not self.controlling
+                        if not self.controlling:
+                            print("disable control")
+                            robot.send_cmd()  # stop robot
+                        else:
+                            print("enable control")
+                            self.t = time.time()
+                    elif key == 48:  # 0
+                        target_pos = np.array([0.0, 0.0, 0.0])  # TODO: use center of board for target pos
+                    elif key == 43:  # +
+                        self.control_scaling += 0.1
+                        self.control_scaling = min(self.control_scaling, 1.0)
+                        print("control scaling = ", self.control_scaling)
+                    elif key == 45:  # -
+                        self.control_scaling -= 0.1
+                        self.control_scaling = max(self.control_scaling, 0.1)
+                        print("control scaling = ", self.control_scaling)
+                    elif key == 9:  # TAB
+                        # switch controlled robot
+                        robot.send_cmd()  # stop current robot
+                        controlled_robot_number = (controlled_robot_number + 1) % len(robots)
+                        robot = robots[controlled_robot_number]
+                        print(f"controlled robot: {robot.id}")
+                    elif key == 113 or key == 27:  # q or ESCAPE
+                        print("quit!")
+                        self.controlling = False
+                        robot.send_cmd()
+                        return
+
+            if self.controlling:
+                # measure state
+                x_pred = self.get_measurement(robot.id)
+
+                # print(np.linalg.norm(x_pred-target_pos))
+
+                # solve mpc open loop problem
+                res = self.ols.solve(x_pred, target_pos)
+
+                us1 = res[0] * self.control_scaling
+                us2 = res[1] * self.control_scaling
+
+                dt_mpc = time.time() - self.t
+                if dt_mpc < self.dt:  # wait until next control can be applied
+                    time.sleep(self.dt - dt_mpc)
+
+                # 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]
+                    robot.send_cmd(u1, u2)
+                    if i < self.mstep:
+                        time.sleep(self.dt)
+                    self.t = time.time()  # save time the most recent control was applied
+
+    def get_measurement(self, robot_id):
+        return self.estimator.get_robot_state_estimate(robot_id)

remote_control/mpc_test.py

@@ -0,0 +1,55 @@
+import sys
+import socket
+import threading
+import time
+
+from robot import Robot
+
+from mpc_controller import MPCController
+
+from aruco_estimator import ArucoEstimator
+
+
+class RemoteController:
+    def __init__(self):
+        self.robots = []
+        #self.robots = [Robot(11, '192.168.1.11'), Robot(13, '192.168.1.13'), Robot(14, '192.168.1.14')]
+
+        self.robot_ids = {}
+        for r in self.robots:
+            self.robot_ids[r.id] = r
+
+        # socket for movement commands
+        self.comm_socket = socket.socket()
+        self.comm_socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
+
+        for robot in self.robots:
+            robot.connect()
+
+        self.comm_socket.bind(('', 1337))
+        self.comm_socket.listen(5)
+
+        self.t = time.time()
+
+        # start thread for marker position detection
+        self.estimator = ArucoEstimator(self.robot_ids.keys())
+        self.estimator_thread = threading.Thread(target=self.estimator.run_tracking)
+        self.estimator_thread.start()
+
+        self.controller = MPCController(self.estimator)
+
+    def run(self):
+        print("waiting until all markers are detected...")
+        while not (self.estimator.all_corners_detected() and self.estimator.all_robots_detected()):
+            pass
+        print("starting control")
+        self.controller.interactive_control(robots=self.robots)
+
+
+def main(args):
+    rc = RemoteController()
+    rc.run()
+
+
+if __name__ == '__main__':
+    main(sys.argv)

remote_control/pid_controller.py

@@ -0,0 +1,267 @@
+import numpy as np
+import math
+import time
+
+
+class PIDController:
+    def __init__(self, estimator):
+        self.t = time.time()
+
+        self.estimator = estimator
+        self.controlling = False
+
+        self.P_angle = 0.4     # PID parameters determined by Ziegler-Nichols. measured K_crit = 1.4, T_crit = 1.5
+        self.I_angle = 0.35
+        self.D_angle = 0.1
+
+        self.P_pos = 0.50
+        self.I_pos = 0.3
+        self.D_pos = 0.1
+
+        self.mode = None
+
+    def move_to_pos(self, target_pos, robot, near_target_counter=5):
+        near_target = 0
+        while near_target < near_target_counter:
+            while not self.estimator.event_queue.empty():
+                event = self.estimator.event_queue.get()
+                print("event: ", event)
+                if event[0] == 'click':
+                    pass
+                elif event[0] == 'key':
+                    key = event[1]
+
+                    if key == 84:  # arrow up
+                        self.controlling = True
+                        self.t = time.time()
+                    elif key == 82:  # arrow down
+                        self.controlling = False
+                        robot.send_cmd()
+                    elif key == 48:  # 0
+                        target_pos = np.array([0.0, 0.0, 0.0])
+                    elif key == 43:  # +
+                        self.control_scaling += 0.1
+                        self.control_scaling = min(self.control_scaling, 1.0)
+                        print("control scaling = ", self.control_scaling)
+                    elif key == 45:  # -
+                        self.control_scaling -= 0.1
+                        self.control_scaling = max(self.control_scaling, 0.1)
+                        print("control scaling = ", self.control_scaling)
+                    elif key == 113:
+                        print("quit!")
+                        self.controlling = False
+                        robot.send_cmd()
+                        return
+                    elif key == 27:  # escape
+                        print("quit!")
+                        self.controlling = False
+                        robot.send_cmd()
+                        return
+
+            x_pred = self.get_measurement(robot.id)
+
+            if x_pred is not None:
+                error_pos = np.linalg.norm(x_pred[0:2] - target_pos[0:2])
+                angles_unwrapped = np.unwrap([x_pred[2], target_pos[2]])  # unwrap angle to avoid jump in data
+                error_ang = np.abs(angles_unwrapped[0] - angles_unwrapped[1])
+                # print("error pos = ", error_pos)
+                # print("error_pos = {}, error_ang = {}".format(error_pos, error_ang))
+
+                # if error_pos > 0.075 or error_ang > 0.35:
+                if error_pos > 0.05 or error_ang > 0.1:
+                    # solve mpc open loop problem
+                    res = self.ols.solve(x_pred, target_pos)
+
+                    # us1 = res[0]
+                    # us2 = res[1]
+                    us1 = res[0] * self.control_scaling
+                    us2 = res[1] * self.control_scaling
+                    # print("u = {}", (us1, us2))
+
+                    # 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
+
+                # 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]
+                    robot.send_cmd(u1, u2)
+                    if i < self.mstep:
+                        time.sleep(self.dt)
+                    self.t = time.time()  # save time the most recent control was applied
+            else:
+                print("robot not detected yet!")
+
+    def interactive_control(self, robots):
+        controlled_robot_number = 0
+        robot = robots[controlled_robot_number]
+
+        ts = []
+        angles = []
+
+        target_pos = np.array([0.0, 0.0, 0.0])
+        e_angle_old = 0.0
+        e_pos_old = 0.0
+
+        i = 0.0
+        i_angle = 0.0
+        i_pos = 0.0
+
+        t0 = time.time()
+
+        running = True
+        while running:
+            # handle events from opencv window
+            while not self.estimator.event_queue.empty():
+                event = self.estimator.event_queue.get()
+                print("event: ", event)
+                if event[0] == 'click':
+                    target_pos = event[1]
+                    i_angle = 0
+                    i_pos = 0
+                    e_pos_old = 0
+                    e_angle_old = 0
+                    self.mode = 'combined'
+                elif event[0] == 'key':
+                    key = event[1]
+
+                    if key == 32:  # arrow up
+                        self.controlling = not self.controlling
+                        if not self.controlling:
+                            print("disable control")
+                            robot.send_cmd()  # stop robot
+                            self.mode = None    # reset control mode
+                        else:
+                            print("enable control")
+                            i = 0
+                            self.t = time.time()
+                    elif key == 48:  # 0
+                        target_pos = np.array([0.0, 0.0, 0.0])  # TODO: use center of board for target pos
+                    elif key == 97:  # a
+                        self.mode = 'angle'
+                        e_angle_old = 0
+                        i = 0
+                        self.t = time.time()
+                    elif key == 99:  # c
+                        self.mode = 'combined'
+                        e_angle_old = 0
+                        e_pos_old = 0
+                        i_angle = 0
+                        i_pos = 0
+                        self.t = time.time()
+                    elif key == 112:  # p
+                        self.mode = 'position'
+                        e_pos_old = 0
+                        i = 0
+                        self.t = time.time()
+                    elif key == 43: # +
+                        self.P_pos += 0.1
+                        print("P = ", self.P_angle)
+                    elif key == 45: # -
+                        self.P_pos -= 0.1
+                        print("P = ", self.P_angle)
+                    elif key == 9:  # TAB
+                        # switch controlled robot
+                        robot.send_cmd()  # stop current robot
+                        controlled_robot_number = (controlled_robot_number + 1) % len(robots)
+                        robot = robots[controlled_robot_number]
+                        print(f"controlled robot: {robot.id}")
+                    elif key == 113 or key == 27:  # q or ESCAPE
+                        print("quit!")
+                        self.controlling = False
+                        robot.send_cmd()
+                        return
+
+            if self.controlling:
+                # measure state
+                x_pred = self.get_measurement(robot.id)
+                dt = self.t - time.time()
+
+
+
+                #print(f"x_pred = {x_pred}\ntarget = {target_pos}\nerror = {np.linalg.norm(target_pos - x_pred)}\n")
+                if self.mode == 'angle':
+                    # compute angle such that robot faces to target point
+                    target_angle = target_pos[2]
+
+                    ts.append(time.time() - t0)
+                    angles.append(x_pred[2])
+
+                    angles_unwrapped = np.unwrap([x_pred[2], target_angle])  # unwrap angle to avoid jump in data
+
+                    e_angle = angles_unwrapped[0] - angles_unwrapped[1]   # angle difference
+                    p = self.P_angle * e_angle
+                    # i += self.I * dt * e     # right Riemann sum
+                    i += self.I_angle * dt * (e_angle + e_angle_old)/2.0  # trapezoidal rule
+                    d = self.D_angle * (e_angle - e_angle_old)/dt
+
+                    u1 = p - i - d
+                    u2 = - u1
+
+                    e_angle_old = e_angle
+
+                elif self.mode == 'combined':
+                    # compute angle such that robot faces to target point
+                    v = target_pos[0:2] - x_pred[0:2]
+                    target_angle = math.atan2(v[1], v[0])
+
+                    angles_unwrapped = np.unwrap([x_pred[2], target_angle])  # unwrap angle to avoid jump in data
+
+                    e_angle = angles_unwrapped[0] - angles_unwrapped[1]  # angle difference
+                    e_pos = np.linalg.norm(v)
+
+                    if e_pos < 0.05:
+                        self.mode = 'angle'
+                        e_angle_old = 0
+                        e_pos_old = 0
+                        i_angle = 0
+                        i_pos = 0
+                        u1 = 0
+                        u2 = 0
+                    else:
+                        forward = abs(e_angle) < np.pi/2.0
+
+                        if not forward:
+                            if e_angle > np.pi/2.0:
+                                e_angle -= np.pi
+                            else:
+                                e_angle += np.pi
+
+                        p_angle = self.P_angle * e_angle
+                        i_angle += self.I_angle * dt * (e_angle + e_angle_old) / 2.0  # trapezoidal rule
+                        d_angle = self.D_angle * (e_angle - e_angle_old) / dt
+
+                        p_pos = self.P_pos * e_pos
+                        i_pos += self.I_pos * dt * (e_pos + e_pos_old) / 2.0  # trapezoidal rule
+                        d_pos = self.D_pos * (e_pos - e_pos_old) / dt
+
+                        if forward:
+                            print("forward")
+                            u1 = p_angle + p_pos - i_angle - i_pos - d_angle - d_pos
+                            u2 = - p_angle + p_pos + i_angle - i_pos + d_angle - d_pos
+                        else:
+                            print("backward")
+                            u1 = p_angle - p_pos - i_angle + i_pos - d_angle + d_pos
+                            u2 = - p_angle - p_pos + i_angle + i_pos + d_angle + d_pos
+
+                        e_pos_old = e_pos
+                        e_angle_old = e_angle
+
+                else:
+                    u1 = 0.0
+                    u2 = 0.0
+                #print(f"u = ({u1}, {u2})")
+                robot.send_cmd(u1, u2)
+                self.t = time.time()  # save time when the most recent control was applied
+                time.sleep(0.1)
+
+
+    def get_measurement(self, robot_id):
+        return self.estimator.get_robot_state_estimate(robot_id)

remote_control/position_controller.py

@@ -30,8 +30,12 @@ from marker_pos_angle.msg import id_pos_angle
 
 from collections import OrderedDict
 
+from argparse import ArgumentParser
+
+
+
 class Robot:
-    def __init__(self, id, ip=None):
+    def __init__(self, id, ip):
         self.pos = None
         self.orient = None
 
@@ -52,16 +56,16 @@ class Track:
     def __init__(self):
         # ids in clockwise direction
         self.inner = OrderedDict()
+        self.inner[0] = None
         self.inner[1] = None
         self.inner[2] = None
         self.inner[3] = None
-        self.inner[4] = None
 
         self.outer = OrderedDict()
+        self.outer[4] = None
         self.outer[5] = None
         self.outer[6] = None
         self.outer[7] = None
-        self.outer[8] = None
 
         self.track_complete = False
 
@@ -122,20 +126,18 @@ def f_ode(t, x, u):
     return dx
 
 class RemoteController:
-    def __init__(self):
+    def __init__(self, id, ip):
 
-        self.robots = [Robot(11, '192.168.1.103')]
+        self.anim_stopped = False
-        #self.robots = [Robot(14, '192.168.1.102')]
+
+        #self.robots = [Robot(14, '192.168.1.103')]
+        #self.robots = [Robot(15, '192.168.1.102')]
+        self.robots = [Robot(id, ip)]
 
         self.robot_ids = {}
         for r in self.robots:
             self.robot_ids[r.id] = r
 
-        obst = [Obstacle(12, 0.275), Obstacle(10, 0.275), Obstacle(14, 0.275), Obstacle(15, 0.275)]
-
-        self.obstacles = {}
-        for r in obst:
-            self.obstacles[r.id] = r
 
         self.track = Track()
 
@@ -198,13 +200,6 @@ class RemoteController:
         self.track_line_inner, = self.ax.plot([], [])
         self.track_line_outer, = 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)
-
         self.ax.set_xlabel('x-position')
         self.ax.set_ylabel('y-position')
         self.ax.grid()
@@ -231,6 +226,7 @@ class RemoteController:
 
 
     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()
@@ -251,10 +247,13 @@ class RemoteController:
         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, self.circles[0], self.circles[1],\
+               self.track_line_inner, self.track_line_outer, self.line_x,self.line_y,
-               self.circles[2], self.circles[3],
 
     def ani_update(self, frame):
+        if self.anim_stopped:
+            self.ani.event_source.stop()
+            sys.exit(0)
+
         #print("plotting")
         self.mutex.acquire()
         try:
@@ -306,21 +305,11 @@ class RemoteController:
             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.track_line_inner, self.track_line_outer,\
-               self.line_x, self.line_y, self.circles[0], self.circles[1],self.circles[2],self.circles[3],
+               self.line_x, self.line_y, 
 
     def measurement_callback(self, data):
         #print(data)
@@ -352,11 +341,6 @@ class RemoteController:
                 finally:
                     self.mutex.release()
 
-        # detect obstacles
-        if data.id in self.obstacles.keys():
-            obst = (data.x, data.y)
-            self.obstacles[data.id].pos = obst
-
         # detect track
         if data.id in self.track.inner.keys() or data.id in self.track.outer.keys():
             self.track.set_id(data)
@@ -369,7 +353,8 @@ class RemoteController:
         markers_out = self.track.outer.values()
 
         # find targets:
-        lamb = 0.2
+        # generate waypoints
+        lamb = 0.5
         j = 0
         for i in range(0,4):
             p = np.array(markers_in[i]) + lamb * (np.array(markers_out[i]) - np.array(markers_in[i]))
@@ -382,9 +367,18 @@ class RemoteController:
                 targets[j] = (mean[0], mean[1], 0.0)
                 j += 1
 
+        # final connection between first and last marker
+        mean_in = (np.array(markers_in[3]) + np.array(markers_in[0])) * 0.5
+        mean_out = (np.array(markers_out[3]) + np.array(markers_out[0])) * 0.5
+        mean = mean_in + (1.0 - lamb) * (mean_out - mean_in)
+        targets[j] = (mean[0], mean[1], 0.0)
+        print("targets = {}".format(targets.keys()))
+
         auto_control = False
         current_target = 0
                 
+        control_scaling = 0.3
+
         while True:
 
             # open loop controller
@@ -418,12 +412,32 @@ class RemoteController:
                         self.target = targets[5]
                     elif event.key == pygame.K_7:
                         self.target = targets[6]
+                    elif event.key == pygame.K_8:
+                        self.target = targets[7]
                     elif event.key == pygame.K_SPACE:
                         auto_control = not auto_control
                         if auto_control:
                             self.target = targets[current_target]
+                    elif event.key == pygame.K_PLUS:
+                        control_scaling += 0.1
+                        control_scaling = min(control_scaling, 1.0)
+                    elif event.key == pygame.K_MINUS:
+                        control_scaling -= 0.1
+                        control_scaling = max(control_scaling, 0.3)
+                    elif event.key == pygame.K_ESCAPE:
+                        print("quit!")
+                        self.controlling = False
+                        if self.rc_socket:
+                            self.rc_socket.send('(0.0,0.0)\n')
+                        self.anim_stopped = True
+                        return
                     elif event.key == pygame.QUIT:
-                        sys.exit(0)
+                        print("quit!")
+                        self.controlling = False
+                        if self.rc_socket:
+                            self.rc_socket.send('(0.0,0.0)\n')
+                        self.anim_stopped = True
+                        return
 
             if self.controlling:
 
@@ -432,17 +446,20 @@ class RemoteController:
                 if auto_control:
                     if np.linalg.norm(x_pred[0:2]-np.array(self.target[0:2])) < 0.3:
                         print("close to target!")
-                        current_target = (current_target + 1) % 7
+                        current_target = (current_target + 1) % 8
                         self.target = targets[current_target]
                         print("new target = {}".format(current_target))
 
                 tmpc_start = time.time()
 
                 # solve mpc open loop problem
-                res = self.ols.solve(x_pred, self.target, self.obstacles, self.track)
+                res = self.ols.solve(x_pred, self.target, [], self.track)
 
-                us1 = res[0]
+                #us1 = res[0]
-                us2 = res[1]
+                #us2 = res[1]
+                us1 = res[0] * control_scaling
+                us2 = res[1] * control_scaling
+                print("u = {}", (us1, us2))
 
                 # save open loop trajectories for plotting
                 self.mutex.acquire()
@@ -493,9 +510,18 @@ class RemoteController:
 
 
 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()
+    rc = RemoteController(marker_id, ip)
 
     pygame.init()
 
@@ -508,7 +534,8 @@ def main(args):
         pass
 
     #threading.Thread(target=rc.input_handling).start()
-    threading.Thread(target=rc.controller).start()
+    controller_thread = threading.Thread(target=rc.controller)
+    controller_thread.start()
 
     rc.ani()
 

remote_control/roborally.py

@@ -0,0 +1,285 @@
+import sys
+import socket
+import threading
+import time
+
+from mpc_controller import MPCController
+from robot import Robot
+from aruco_estimator import ArucoEstimator
+
+MSGLEN = 64
+
+def myreceive(sock):
+    chunks = []
+    bytes_recd = 0
+    while bytes_recd < MSGLEN:
+        chunk = sock.recv(1)
+        if chunk == b'':
+            raise RuntimeError("socket connection broken")
+        chunks.append(chunk)
+        bytes_recd = bytes_recd + len(chunk)
+
+        if chunks[-1] == b'\n':
+            break
+
+    return b''.join(chunks)
+
+
+class RoboRallyRobot(Robot):
+    # dictionary mapping the current orientation and a turn command to the resulting orientation
+    resulting_orientation = {
+        '^': {'turn left': '<', 'turn right': '>', 'turn around': 'v'},
+        '>': {'turn left': '^', 'turn right': 'v', 'turn around': '<'},
+        'v': {'turn left': '>', 'turn right': '<', 'turn around': '^'},
+        '<': {'turn left': 'v', 'turn right': '^', 'turn around': '>'},
+    }
+
+    # dictionary mapping an orientation to its opposite
+    opposites = {'^': 'v', '>': '<', 'v': '^', '<': '>'}
+
+    def __init__(self, id, ip, x, y, orientation):
+        super().__init__(id, ip)
+
+        self.grid_x = x
+        self.grid_y = y
+        self.grid_orientation = orientation
+
+    def get_neighbor_coordinates(self, direction):
+        # get the coordinates of the neighboring tile in the given direction
+        if direction == '^':
+            return self.grid_x, self.grid_y - 1
+        elif direction == '>':
+            return self.grid_x + 1, self.grid_y
+        elif direction == 'v':
+            return self.grid_x, self.grid_y + 1
+        elif direction == '<':
+            return self.grid_x - 1, self.grid_y
+        else:
+            print("error: unknown direction")
+            sys.exit(1)
+
+    def move(self, move_type):
+        if move_type == 'forward':
+            target_tile = self.get_neighbor_coordinates(self.grid_orientation)
+            self.grid_x = target_tile[0]
+            self.grid_y = target_tile[1]
+        elif move_type == 'backward':
+            opposite_orientation = RoboRallyRobot.opposites[self.grid_orientation]
+            target_tile = self.get_neighbor_coordinates(opposite_orientation)
+            self.grid_x = target_tile[0]
+            self.grid_y = target_tile[1]
+        elif 'turn' in move_type:
+            self.grid_orientation = RoboRallyRobot.resulting_orientation[self.grid_orientation][move_type]
+        elif 'nop' in move_type:
+            pass    # nop command -> robot grid position does not change (used e.g. for driving the robot to initial
+                    #                                                      position)
+        else:
+            print(f"error: invalid move: {move_type}")
+            sys.exit(1)
+
+    def __str__(self):
+        return self.__repr__()
+
+    def __repr__(self):
+        return f"grid x: {self.grid_x}, grid y: {self.grid_y}, grid orientation: {self.grid_orientation}"
+
+
+class RemoteController:
+    valid_cmds = ['forward', 'backward', 'turn left', 'turn right', 'turn around', 'nop', 'get position',
+                  'set position', 'initialize_robot', 'initialize_grid']
+
+    def __init__(self):
+        self.robots = []
+        #self.robots = [RoboRallyRobot(12, '192.168.1.12', x=1, y=1, orientation='>')]
+
+        self.robot_ids = {}
+        for r in self.robots:
+            self.robot_ids[r.id] = r
+
+        # socket for movement commands
+        self.comm_socket = socket.socket()
+        self.comm_socket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1)
+
+        for robot in self.robots:
+            robot.connect()
+
+        self.comm_socket.bind(('', 1337))
+        self.comm_socket.listen(5)
+
+        self.t = time.time()
+
+        # start thread for marker position detection
+        self.estimator = ArucoEstimator(self.robot_ids.keys())
+        self.estimator_thread = threading.Thread(target=self.estimator.run_tracking)
+        self.estimator_thread.start()
+
+        self.controller = MPCController(self.estimator)
+
+        print("waiting for corner and robot detection..")
+        while not self.estimator.all_robots_detected() or not self.estimator.all_corners_detected():
+            pass
+        print("everything detected!")
+        # drive robots to initial position
+        for robot_id in self.robot_ids:
+            self.grid_control(robot_id, 'nop')
+
+    def run(self):
+        print("waiting until all markers are detected...")
+        while not self.estimator.all_corners_detected():
+            pass
+        print("starting control")
+
+        running = True
+        while running:
+            (clientsocket, address) = self.comm_socket.accept()
+            clientsocket.settimeout(None)
+
+            connected = True
+            while connected:
+                try:
+                    data = myreceive(clientsocket)
+                    print("data received: ", data)
+
+                    inputs = data.split(b',')
+                    cmd = inputs[0]
+                    cmd = cmd.strip().decode()
+
+                    if len(inputs) > 1:
+                        if cmd in RemoteController.valid_cmds:
+                            if cmd == 'initialize_grid':
+                                try:
+                                    grid_columns = int(inputs[1])
+                                    grid_rows = int(inputs[2])
+
+                                    self.estimator.grid_columns = grid_columns
+                                    self.estimator.grid_rows = grid_rows
+                                    clientsocket.sendall(b'OK\n')
+                                except ValueError:
+                                    print("could not initialize grid!")
+                                    clientsocket.sendall(b'"could not initialize grid!\n'
+                                                         b'expected: initialize_robot, <grid columns>, <grid rows>')
+                                except IndexError:
+                                    print("could not initialize grid!")
+                                    clientsocket.sendall(b'"could not initialize grid!\n'
+                                                         b'expected: initialize_robot, <grid columns>, <grid rows>')
+                            else:   # robot command
+                                try:
+                                    robot_id = int(inputs[1])
+                                except ValueError:
+                                    robot_id = None
+                                    print("could not read robot id!")
+                                    clientsocket.sendall(b'Could not read robot id!\n')
+
+                                if cmd == 'initialize_robot':
+                                    # add a new robot to the game
+                                    try:
+                                        id = int(inputs[1])
+                                        ip = inputs[2].decode().strip()
+                                        x = int(inputs[3])
+                                        y = int(inputs[4])
+                                        orientation = inputs[5].decode().strip()
+
+                                        print(f"initializing new robot with id {id} and ip {ip} at pos ({x},{y}) with "
+                                              f"orientation '{orientation}'")
+                                        if id not in self.robot_ids:
+                                            new_robot = RoboRallyRobot(id=id, ip=ip, x=x, y=y, orientation=orientation)
+                                            new_robot.connect()
+
+                                            # store the new robot in the list of robots
+                                            self.robots.append(new_robot)
+                                            self.robot_ids[new_robot.id] = new_robot  # this also means the estimator
+                                            # will track the new robot because
+                                            # it got a reference to the list of
+                                            # robot ids to keep an eye out for
+
+                                        else: # robot is already created -> just re-initialize its position
+                                            new_robot = self.robot_ids[id]
+                                            new_robot.grid_x = x
+                                            new_robot.grid_y = y
+                                            new_robot.orientation = orientation
+
+                                        if new_robot.connected:
+                                            print("created new robot and successfully connected to it!")
+
+                                            while not self.estimator.all_robots_detected(): # wait until the robot gets detected
+                                                pass
+
+                                            # drive the new robot to its starting position
+                                            self.grid_control(new_robot.id, 'nop')
+
+                                            clientsocket.sendall(b'OK\n')
+                                        else:
+                                            clientsocket.sendall(f"error: could not connect to new robot {new_robot}".encode())
+
+                                    except IndexError:
+                                        print("could not initialize a new robot")
+                                        clientsocket.sendall('could not initialize a new robot: invalid command format\n'
+                                            'expected: initialize_robot, <id>, <ip>, <x>, <y>, <orientation>\n'.encode())
+                                    except ValueError:
+                                        print("could not initialize a new robot")
+                                        clientsocket.sendall('could not initialize a new robot: invalid command format\n'
+                                            'expected: initialize_robot, <id>, <ip>, <x>, <y>, <orientation>\n'.encode())
+
+                                elif robot_id in self.robot_ids:
+                                    if cmd == b'get position':
+                                        clientsocket.sendall(bytes('{}\n'.format(self.robot_ids[robot_id].grid_pos)))
+                                    elif cmd == b'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
+                                            clientsocket.sendall(b'OK\n')
+                                        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.grid_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 b'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 grid_control(self, robot_id, cmd):
+        robot = self.robot_ids[robot_id]  # get robot to be controlled
+
+        print("robot grid pos before move: ", robot)
+        robot.move(cmd)
+        print("robot grid pos after move: ", robot)
+
+        target = self.estimator.get_pos_from_grid_point(robot.grid_x, robot.grid_y, robot.grid_orientation)
+
+        self.controller.move_to_pos(target, robot)
+
+
+def main(args):
+    rc = RemoteController()
+    rc.run()
+
+
+if __name__ == '__main__':
+    main(sys.argv)

remote_control/robot.py

@@ -0,0 +1,37 @@
+import socket
+
+class Robot:
+    def __init__(self, marker_id, ip):
+        self.id = marker_id
+        self.pos = None
+        self.euler = None
+
+        self.ip = ip
+        self.socket = socket.socket()
+
+        # currently active control
+        self.u1 = 0.0
+        self.u2 = 0.0
+
+        self.connected = False
+
+    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!")
+            self.connected = True
+        except socket.error:
+            print("could not connect to robot {} with ip {}".format(self.id, self.ip))
+
+    def send_cmd(self, u1=0.0, u2=0.0):
+        if self.socket:
+            try:
+                self.socket.send(f'({u1},{u2})\n'.encode())
+            except BrokenPipeError:
+                print(f"error: connection to robot {self.id} with ip {self.ip} lost")
+                pass
+            except ConnectionResetError:
+                print(f"error: connection to robot {self.id} with ip {self.ip} lost")
+                pass