input handling using opencv window
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102
remote_control/mpc_controller.py
Normal file
102
remote_control/mpc_controller.py
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@ -0,0 +1,102 @@
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import numpy as np
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import time
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from casadi_opt import OpenLoopSolver
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class MPCController:
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def __init__(self, estimator):
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self.t = time.time()
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self.estimator = estimator
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self.controlling = False
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self.mstep = 2
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self.ols = OpenLoopSolver(N=20, T=1.0)
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self.ols.setup()
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self.dt = self.ols.T / self.ols.N
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# integrator
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self.omega_max = 5.0
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self.control_scaling = 0.2
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def move_to_pos(self, target_pos, robot, near_target_counter=5):
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near_target = 0
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while near_target < near_target_counter:
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while not self.estimator.event_queue.empty():
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event = self.estimator.event_queue.get()
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print("event: ", event)
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if event[0] == 'click':
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pass
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elif event[0] == 'key':
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key = event[1]
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if key == 84: # arrow up
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self.controlling = True
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self.t = time.time()
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elif key == 82: # arrow down
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self.controlling = False
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robot.send_cmd()
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elif key == 48: # 0
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target_pos = np.array([0.0,0.0,0.0])
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elif key == 43: # +
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self.control_scaling += 0.1
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self.control_scaling = min(self.control_scaling, 1.0)
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print("control scaling = ", self.control_scaling)
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elif key == 45: # -
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self.control_scaling -= 0.1
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self.control_scaling = max(self.control_scaling, 0.1)
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print("control scaling = ", self.control_scaling)
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elif key == 113:
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print("quit!")
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self.controlling = False
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robot.send_cmd()
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return
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elif key == 27: # escape
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print("quit!")
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self.controlling = False
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robot.send_cmd()
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self.anim_stopped = True
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return
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x_pred = self.get_measurement(robot.id)
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error_pos = np.linalg.norm(x_pred[0:2] - target_pos[0:2])
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angles_unwrapped = np.unwrap([x_pred[2], target_pos[2]]) # unwrap angle to avoid jump in data
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error_ang = np.abs(angles_unwrapped[0] - angles_unwrapped[1])
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#print("error pos = ", error_pos)
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#print("error_pos = {}, error_ang = {}".format(error_pos, error_ang))
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#if error_pos > 0.075 or error_ang > 0.35:
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if error_pos > 0.05 or error_ang > 0.2:
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# solve mpc open loop problem
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res = self.ols.solve(x_pred, target_pos)
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#us1 = res[0]
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#us2 = res[1]
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us1 = res[0] * self.control_scaling
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us2 = res[1] * self.control_scaling
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#print("u = {}", (us1, us2))
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tmpc_end = time.time()
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#print("---------------- mpc solution took {} seconds".format(tmpc_end - tmpc_start))
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dt_mpc = time.time() - self.t
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if dt_mpc < self.dt: # wait until next control can be applied
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#print("sleeping for {} seconds...".format(self.dt - dt_mpc))
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time.sleep(self.dt - dt_mpc)
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else:
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us1 = [0] * self.mstep
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us2 = [0] * self.mstep
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near_target += 1
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# send controls to the robot
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for i in range(0, self.mstep): # option to use multistep mpc if len(range) > 1
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u1 = us1[i]
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u2 = us2[i]
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robot.send_cmd(u1, u2)
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if i < self.mstep:
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time.sleep(self.dt)
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self.t = time.time() # save time the most recent control was applied
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def get_measurement(self, robot_id):
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return np.array(self.estimator.get_robot_state_estimate(robot_id))
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@ -3,6 +3,7 @@ import numpy as np
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import cv2
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from cv2 import aruco
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from shapely.geometry import LineString
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from queue import Queue
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DS5_product_ids = ["0AD1", "0AD2", "0AD3", "0AD4", "0AD5", "0AF6", "0AFE", "0AFF", "0B00", "0B01", "0B03", "0B07","0B3A"]
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@ -42,6 +43,8 @@ class ArucoEstimator:
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self.robot_marker_ids = robot_marker_ids
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self.robot_marker_estimates = dict([(id, None) for id in self.robot_marker_ids])
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self.event_queue = Queue()
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if False: # check if realsense camera is connected
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# Configure depth and color streams
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self.pipeline = rs.pipeline()
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@ -68,9 +71,18 @@ class ArucoEstimator:
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self.cv_camera = cv2.VideoCapture(0)
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self.pipeline = None
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def mouse_callback(self, event, x, y, flags, param):
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if event == 1:
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print(event)
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self.event_queue.put(('click', (x,y)))
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def run_tracking(self):
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cv2.namedWindow('RoboRally', cv2.WINDOW_AUTOSIZE)
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cv2.setMouseCallback('RoboRally', self.mouse_callback)
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try:
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while True:
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running = True
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while running:
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if self.pipeline:
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frames = self.pipeline.wait_for_frames()
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color_frame = frames.get_color_frame()
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@ -113,11 +125,16 @@ class ArucoEstimator:
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tvec=np.array([1.2, 0.42, 0]))
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# Show images
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cv2.namedWindow('RealSense', cv2.WINDOW_AUTOSIZE)
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cv2.imshow('RealSense', frame)
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cv2.waitKey(1)
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cv2.imshow('RoboRally', frame)
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key = cv2.waitKey(1)
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if key > 0:
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self.event_queue.put(('key', key))
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print('key = ', key)
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if key == ord('q'):
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running = False
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finally:
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cv2.destroyAllWindows()
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if self.pipeline is not None:
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# Stop streaming
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self.pipeline.stop()
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@ -304,3 +321,5 @@ class ArucoEstimator:
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if __name__ == "__main__":
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estimator = ArucoEstimator()
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estimator.run_tracking()
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@ -1,36 +1,9 @@
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# startup:
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# roscore -> start ros
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# rosparam set cv_camera/device_id 0 -> set appropriate camera device
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# rosrun cv_camera cv_camera_node -> start the camera
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# roslaunch aruco_detect aruco_detect.launch camera:=cv_camera image:=image_raw dictionary:=16 transport:= fiducial_len:=0.1 # aruco marker detection
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# python fiducial_to_2d_pos_angle.py -> compute position and angle of markers in 2d plane
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import sys
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import rospy
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import pygame
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import numpy as np
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import socket
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import scipy.integrate
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import copy
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import threading
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from copy import deepcopy
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import matplotlib.pyplot as plt
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import matplotlib.animation as anim
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import matplotlib.patches as patch
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from shapely.geometry import Polygon
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import time
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from casadi_opt import OpenLoopSolver
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#from marker_pos_angle.msg import id_pos_angle
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from collections import OrderedDict
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from argparse import ArgumentParser
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from mpc_controller import MPCController
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import opencv_viewer_example
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@ -76,12 +49,6 @@ class Robot:
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self.ip = ip
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self.socket = socket.socket()
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# variables for measurements
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self.tms_0 = None
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self.xm_0 = None
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self.tms = None
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self.xms = None
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# currently active control
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self.u1 = 0.0
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self.u2 = 0.0
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@ -126,36 +93,23 @@ class Robot:
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print("could not connect to robot {} with ip {}".format(self.id, self.ip))
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sys.exit(1)
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def send_cmd(self, u1=0.0, u2=0.0):
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if self.socket:
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try:
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self.socket.send(f'({u1},{u2})\n'.encode())
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except BrokenPipeError:
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#print(f"error: connection to robot {self.id} with ip {self.ip} lost")
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pass
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def __str__(self):
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return self.__repr__()
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def __repr__(self):
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return f"x: {self.x}, y: {self.y}, orienation: {self.orientation}"
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def f_ode(t, x, u):
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# dynamical model of the two-wheeled robot
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# TODO: find exact values for these parameters
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r = 0.03
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R = 0.05
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d = 0.02
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theta = x[2]
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omega_r = u[0]
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omega_l = u[1]
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dx = np.zeros(3)
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dx[0] = (r/2.0 * np.cos(theta) - r*d/(2.0*R) * np.sin(theta)) * omega_r \
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+ (r/2.0 * np.cos(theta) + r*d/(2.0 * R) * np.sin(theta)) * omega_l
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dx[1] = (r/2.0 * np.sin(theta) + r*d/(2.0*R) * np.cos(theta)) * omega_r \
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+ (r/2 * np.sin(theta) - r*d/(2.0*R) * np.cos(theta)) * omega_l
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dx[2] = -r/(2.0*R) * (omega_r - omega_l)
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return dx
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class RemoteController:
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def __init__(self, id, ip):
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def __init__(self):
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# self.robots = #[Robot(11, '192.168.1.11', (6, -3, np.pi)), Robot(12, '192.168.1.12', (6, -3, np.pi)),
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# Robot(13, '192.168.1.13', (6, -3, np.pi)), Robot(14, '192.168.1.14', (6, -2, np.pi))]
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#self.robots = [Robot(13, '192.168.1.13', (6, -3, np.pi))]
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@ -182,38 +136,14 @@ class RemoteController:
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self.t = time.time()
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# variables for simulated state
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self.x0 = None
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self.ts = np.array([])
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self.xs = []
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# variable for mpc open loop
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self.ol_x = None
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self.ol_y = None
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# ROS subscriber for detected markers
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# start thread for marker position detection
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self.estimator = opencv_viewer_example.ArucoEstimator(self.robot_ids.keys())
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self.estimator_thread = threading.Thread(target=self.estimator.run_tracking)
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self.estimator_thread.start()
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# pid parameters
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self.controlling = False
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self.controller = MPCController(self.estimator)
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self.mstep = 2
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self.ols = OpenLoopSolver(N=20, T=1.0)
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self.ols.setup()
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self.dt = self.ols.T / self.ols.N
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self.target = (0.0, 0.0, 0.0)
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# integrator
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self.r = scipy.integrate.ode(f_ode)
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self.omega_max = 5.0
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self.control_scaling = 0.2
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#self.omega_max = 13.32
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def controller(self):
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def run(self):
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print("waiting until all markers are detected...")
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while not self.estimator.all_corners_detected():
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pass
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@ -260,7 +190,7 @@ class RemoteController:
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print("could not set grid position!")
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clientsocket.sendall(bytes('could not set grid position! (invalid format)\n'.format(self.robot_ids[robot_id].grid_pos)))
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else:
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self.mpc_control(robot_id, cmd)
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self.grid_control(robot_id, cmd)
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clientsocket.sendall(b'OK\n')
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else:
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print("invalid robot id!")
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@ -283,123 +213,21 @@ class RemoteController:
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connected = False
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clientsocket.close()
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def mpc_control(self, robot_id, cmd):
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def grid_control(self, robot_id, cmd):
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robot = self.robot_ids[robot_id] # get robot to be controlled
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print("robot grid pos before move: ", robot)
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robot.move(cmd)
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print("robot grid pos after move: ", robot)
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self.target = self.estimator.get_pos_from_grid_point(robot.x, robot.y, robot.orientation)
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target = self.estimator.get_pos_from_grid_point(robot.x, robot.y, robot.orientation)
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self.pid = False
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self.mpc = True
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near_target = 0
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while near_target < 5:
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# open loop controller
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events = pygame.event.get()
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for event in events:
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if event.type == pygame.KEYDOWN:
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if event.key == pygame.K_UP:
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self.controlling = True
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self.t = time.time()
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elif event.key == pygame.K_DOWN:
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self.controlling = False
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if self.robot_ids[robot_id].socket:
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self.robot_ids[robot_id].socket.send('(0.0,0.0)\n')
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elif event.key == pygame.K_0:
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self.target = np.array([0,0,0])
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elif event.key == pygame.K_PLUS:
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self.control_scaling += 0.1
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self.control_scaling = min(self.control_scaling, 1.0)
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print("control scaling = ", self.control_scaling)
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elif event.key == pygame.K_MINUS:
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self.control_scaling -= 0.1
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self.control_scaling = max(self.control_scaling, 0.1)
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print("control scaling = ", self.control_scaling)
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elif event.key == pygame.K_ESCAPE:
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print("quit!")
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self.controlling = False
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if self.robot_ids[robot_id].socket:
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self.robot_ids[robot_id].socket.send('(0.0,0.0)\n')
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self.anim_stopped = True
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return
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elif event.key == pygame.QUIT:
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print("quit!")
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self.controlling = False
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if self.robot_ids[robot_id].socket:
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self.robot_ids[robot_id].socket.send('(0.0,0.0)\n')
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self.anim_stopped = True
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return
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if self.mpc:
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x_pred = self.get_measurement(robot_id)
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tmpc_start = time.time()
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error_pos = np.linalg.norm(x_pred[0:2] - self.target[0:2])
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angles_unwrapped = np.unwrap([x_pred[2], self.target[2]]) # unwrap angle to avoid jump in data
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error_ang = np.abs(angles_unwrapped[0] - angles_unwrapped[1])
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#print("error pos = ", error_pos)
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#print("error_pos = {}, error_ang = {}".format(error_pos, error_ang))
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#if error_pos > 0.075 or error_ang > 0.35:
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if error_pos > 0.05 or error_ang > 0.2:
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# solve mpc open loop problem
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res = self.ols.solve(x_pred, self.target)
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#us1 = res[0]
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#us2 = res[1]
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us1 = res[0] * self.control_scaling
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us2 = res[1] * self.control_scaling
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#print("u = {}", (us1, us2))
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tmpc_end = time.time()
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#print("---------------- mpc solution took {} seconds".format(tmpc_end - tmpc_start))
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dt_mpc = time.time() - self.t
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if dt_mpc < self.dt: # wait until next control can be applied
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#print("sleeping for {} seconds...".format(self.dt - dt_mpc))
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time.sleep(self.dt - dt_mpc)
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else:
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us1 = [0] * self.mstep
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us2 = [0] * self.mstep
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near_target += 1
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# send controls to the robot
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for i in range(0, self.mstep): # option to use multistep mpc if len(range) > 1
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u1 = us1[i]
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u2 = us2[i]
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if self.robot_ids[robot_id].socket:
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#self.robot_ids[robot_id].socket.send('({},{})\n'.format(u1, u2).encode())
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if i < self.mstep:
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time.sleep(self.dt)
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self.t = time.time() # save time the most recent control was applied
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def get_measurement(self, robot_id):
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return np.array(self.estimator.get_robot_state_estimate(robot_id))
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self.controller.move_to_pos(target, robot)
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def main(args):
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parser = ArgumentParser()
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parser.add_argument('id', metavar='id', type=str, help='marker id of the controlled robot')
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parser.add_argument('ip', metavar='ip', type=str, help='ip address of the controlled robot')
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args = parser.parse_args()
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rc = RemoteController()
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marker_id = int(args.id)
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ip = args.ip
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rc = RemoteController(marker_id, ip)
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pygame.init()
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screenheight = 480
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screenwidth = 640
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pygame.display.set_mode([screenwidth, screenheight])
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rc.controller()
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rc.run()
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if __name__ == '__main__':
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main(sys.argv)
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Reference in New Issue
Block a user