scripts/dwm1000.py

   1 #!/usr/bin/env python
   2 # -*- coding: iso-8859-15 -*-
   3
   4 VISULAIZE = False
   5
   6 import threading
   7 import struct
   8 import rospy
   9 import tf
  10 import numpy as np
  11 from math import *
  12 from i2c import i2c
  13 from time import sleep
  14 from std_msgs.msg import Float32
  15 from nav_msgs.msg import Odometry
  16 if VISULAIZE:
  17         import matplotlib.pyplot as plt
  18
  19 class simple_kalman:
  20         def __init__(self, x_est, P_est, Q, R):
  21                 self.x_est = x_est # Systemzustand
  22                 self.P_est = P_est # Fehlerkovarianz
  23                 self.Q = Q # Systemrauschen
  24                 self.R = R # Varianz des Messfehlers
  25
  26         def run(self, y):
  27                 # Korrektur mit der Messung
  28                 # (1) Berechnung der Kalman Verstärkung
  29                 K = self.P_est/(self.R + self.P_est)
  30                 # (2) Korrektur der Schätzung mit der Messung y
  31                 x = self.x_est + K*(y - self.x_est)
  32                 # (3) Korrektur der Fehlerkovarianzmatrix
  33                 P = (1-K)*self.P_est
  34                 #
  35                 # Prädiktion
  36                 # (1) Prädiziere den Systemzustand
  37                 self.x_est = x
  38                 # (2) Präzidiere die Fehlerkovarianzmatrix
  39                 self.P_est = P + self.Q
  40
  41                 return x
  42
  43 class DW1000(threading.Thread):
  44         def __init__(self, name, addr, offset):
  45                 threading.Thread.__init__(self)
  46                 self.setDaemon(1)
  47                 self.dist = 0
  48                 self.offset = offset
  49                 self.addr = addr
  50                 self.name = name
  51
  52                 self.pub = rospy.Publisher(name, Float32, queue_size=16)
  53
  54                 self.start()
  55
  56         def get_value(self):
  57                 dev = i2c(self.addr)
  58                 ret = struct.unpack("f", dev.read(4))
  59                 dev.close()
  60                 return ret[0]
  61
  62         def distance(self):
  63                 return self.dist
  64
  65         def run(self):
  66                 last_val = 10
  67                 while True:
  68                         val = self.get_value()
  69                         if abs(val - last_val)  > 10:
  70                                 print "Ignoring values too far apart %s: %.2f - %.2f" % (self.name, val, last_val)
  71                         elif not isnan(val):
  72                                 self.dist = val + self.offset
  73                                 self.pub.publish(self.distance())
  74                                 last_val = val
  75                         sleep(0.1)
  76
  77 class Position:
  78         def __init__(self):
  79                 # Varianz des Messfehlers
  80                 Rx = 0.2
  81                 Ry = 0.05
  82                 # Fehlerkovarianz
  83                 P_est_x = 0.02
  84                 P_est_y = 0.01
  85                 # Systemrauschen
  86                 Q = 0.002
  87                 self.filter_x = simple_kalman(1.0, P_est_x, Q, Rx)
  88                 self.filter_y = simple_kalman(0.0, P_est_y, Q, Ry)
  89                 self.speed_x = 0
  90                 self.speed_y = 0
  91                 self.speed_z = 0
  92                 self.last_time = rospy.Time.now()
  93                 rospy.Subscriber("/odom_combined", Odometry, self.odomReceived)
  94
  95         def odomReceived(self, msg):
  96                 self.speed_x = msg.twist.twist.linear.x
  97                 self.speed_y = msg.twist.twist.linear.y
  98                 self.speed_z = msg.twist.twist.angular.z
  99
 100         def filter(self, x, y):
 101                 # Correct estimation with speed
 102                 current_time = rospy.Time.now()
 103                 dt = (current_time - self.last_time).to_sec()
 104                 # Subtract vehicle speed
 105                 pos = np.array([self.filter_x.x_est, self.filter_y.x_est])
 106                 # translation
 107                 pos -= np.array([self.speed_x*dt, self.speed_y*dt])
 108                 # rotation
 109                 rot = np.array([[np.cos(self.speed_z*dt), -np.sin(self.speed_z*dt)],
 110                                 [np.sin(self.speed_z*dt),  np.cos(self.speed_z*dt)]])
 111                 pos = np.dot(pos, rot)
 112                 # copy back
 113                 self.filter_x.x_est = pos[0]
 114                 self.filter_y.x_est = pos[1]
 115
 116                 # run kalman
 117                 x = self.filter_x.run(x)
 118                 y = self.filter_y.run(y)
 119
 120                 self.last_time = current_time
 121                 return x,y
 122
 123
 124 if __name__ == "__main__":
 125         rospy.init_node('DW1000')
 126         dwleft  = DW1000("uwb_dist_left",  0xc2, +0.0)
 127         dwright = DW1000("uwb_dist_right", 0xc0, -0.0)
 128         dist_l_r = 0.285
 129         rate = rospy.Rate(10)
 130         pos = Position()
 131         tf_broadcaster = tf.broadcaster.TransformBroadcaster()
 132
 133         while not rospy.is_shutdown() and dwleft.is_alive() and dwright.is_alive():
 134                 dist_left = dwleft.distance()
 135                 dist_right = dwright.distance()
 136                 dir = "left" if (dist_left < dist_right) else "right"
 137
 138                 diff = abs(dist_left - dist_right)
 139                 if diff >= dist_l_r:
 140                         # difference to high, correct to maximum
 141                         off = diff - dist_l_r + 0.01
 142                         if dist_left > dist_right:
 143                                 dist_left -= off/2
 144                                 dist_right += off/2
 145                         else:
 146                                 dist_left += off/2
 147                                 dist_right -= off/2
 148                 print "%.2f %.2f %.2f %.2f %s" % (dwleft.distance(), dwright.distance(), dist_left, dist_right, dir)
 149
 150                 a_r = (-dist_right**2 + dist_left**2 - dist_l_r**2) / (-2*dist_l_r)
 151                 x = dist_l_r/2 - a_r
 152                 t = dist_right**2 - a_r**2
 153                 if t >= 0:
 154                         y = sqrt(t)
 155                         print x,y
 156                         # Rotate 90 deg
 157                         x, y = (y, -x)
 158
 159                         x, y = pos.filter(x, y)
 160                         tf_broadcaster.sendTransform((x, y, 0.0), (0, 0, 0, 1), rospy.Time.now(), "uwb_beacon", "base_footprint")
 161
 162                         if VISULAIZE:
 163                                 circle_left = plt.Circle((-dist_l_r/2, 0), dwleft.distance, color='red', fill=False)
 164                                 circle_right = plt.Circle((dist_l_r/2, 0), dwright.distance, color='green', fill=False)
 165                                 plt.gca().add_patch(circle_left)
 166                                 plt.gca().add_patch(circle_right)
 167                                 plt.grid(True)
 168                                 plt.axis('scaled')
 169                                 plt.show()
 170
 171                 rate.sleep()