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 datetime import datetime
  13 from i2c import i2c
  14 from time import sleep
  15 from std_msgs.msg import Float32
  16 from nav_msgs.msg import Odometry
  17 from wild_thumper.srv import DWM1000Center, DWM1000CenterResponse
  18 if VISULAIZE:
  19         import matplotlib.pyplot as plt
  20
  21 class simple_kalman:
  22         def __init__(self, x_est, P_est, Q, R):
  23                 self.x_est = x_est # Systemzustand
  24                 self.P_est = P_est # Fehlerkovarianz
  25                 self.Q = Q # Systemrauschen
  26                 self.R = R # Varianz des Messfehlers
  27
  28         def run(self, y):
  29                 # Korrektur mit der Messung
  30                 # (1) Berechnung der Kalman Verstärkung
  31                 K = self.P_est/(self.R + self.P_est)
  32                 # (2) Korrektur der Schätzung mit der Messung y
  33                 x = self.x_est + K*(y - self.x_est)
  34                 # (3) Korrektur der Fehlerkovarianzmatrix
  35                 P = (1-K)*self.P_est
  36                 #
  37                 # Prädiktion
  38                 # (1) Prädiziere den Systemzustand
  39                 self.x_est = x
  40                 # (2) Präzidiere die Fehlerkovarianzmatrix
  41                 self.P_est = P + self.Q
  42
  43                 return x
  44
  45 class DW1000(threading.Thread):
  46         def __init__(self, name, addr, offset):
  47                 threading.Thread.__init__(self)
  48                 self.setDaemon(1)
  49                 self.dist = 0
  50                 self.offset = offset
  51                 self.addr = addr
  52                 self.name = name
  53                 self.last_update = datetime.min
  54
  55                 self.pub = rospy.Publisher(name, Float32, queue_size=16)
  56
  57                 self.start()
  58
  59         def get_value(self):
  60                 dev = i2c(self.addr)
  61                 ret = struct.unpack("f", dev.read(4))
  62                 dev.close()
  63                 return ret[0]
  64
  65         def distance(self):
  66                 return self.dist
  67
  68         # Returns each distance only if current
  69         def distance_valid(self):
  70                 if (datetime.now() - self.last_update).seconds < 1:
  71                         return self.dist
  72                 return None
  73
  74         def run(self):
  75                 last_val = 10
  76                 while True:
  77                         val = self.get_value()
  78                         if abs(val - last_val)  > 10:
  79                                 print "Ignoring values too far apart %s: %.2f - %.2f" % (self.name, val, last_val)
  80                         elif not isnan(val):
  81                                 self.dist = val + self.offset
  82                                 self.last_update = datetime.now()
  83                                 self.pub.publish(self.distance())
  84                                 last_val = val
  85                         sleep(0.1)
  86
  87 class Position:
  88         def __init__(self):
  89                 # Varianz des Messfehlers
  90                 Rx = 0.2
  91                 Ry = 0.05
  92                 # Fehlerkovarianz
  93                 P_est_x = 0.02
  94                 P_est_y = 0.01
  95                 # Systemrauschen
  96                 Q = 0.002
  97                 self.filter_x = simple_kalman(1.0, P_est_x, Q, Rx)
  98                 self.filter_y = simple_kalman(0.0, P_est_y, Q, Ry)
  99                 self.speed_x = 0
 100                 self.speed_y = 0
 101                 self.speed_z = 0
 102                 self.last_time = rospy.Time.now()
 103                 rospy.Subscriber("/odom_combined", Odometry, self.odomReceived)
 104
 105         def odomReceived(self, msg):
 106                 self.speed_x = msg.twist.twist.linear.x
 107                 self.speed_y = msg.twist.twist.linear.y
 108                 self.speed_z = msg.twist.twist.angular.z
 109
 110         """
 111         TODO:
 112         - variance of kalman should be dependant on distance
 113         """
 114         def filter(self, x, y):
 115                 # Correct estimation with speed
 116                 current_time = rospy.Time.now()
 117                 dt = (current_time - self.last_time).to_sec()
 118                 # Subtract vehicle speed
 119                 pos = np.array([self.filter_x.x_est, self.filter_y.x_est])
 120                 # translation
 121                 pos -= np.array([self.speed_x*dt, self.speed_y*dt])
 122                 # rotation
 123                 rot = np.array([[np.cos(self.speed_z*dt), -np.sin(self.speed_z*dt)],
 124                                 [np.sin(self.speed_z*dt),  np.cos(self.speed_z*dt)]])
 125                 pos = np.dot(pos, rot)
 126                 # copy back
 127                 self.filter_x.x_est = pos[0]
 128                 self.filter_y.x_est = pos[1]
 129
 130                 # run kalman if new measurements are valid
 131                 if x != None and y != None:
 132                         x = self.filter_x.run(x)
 133                         y = self.filter_y.run(y)
 134                 else:
 135                         x = self.filter_x.x_est
 136                         y = self.filter_y.x_est
 137
 138                 self.last_time = current_time
 139                 return x,y
 140
 141
 142 def handle_center_call(req):
 143         diff = dwleft.distance_valid() - dwright.distance_valid()
 144         dwleft.offset -= diff/2
 145         dwright.offset += diff/2
 146         print "Centering to %.2f %.2f" % (dwleft.offset, dwright.offset)
 147         return DWM1000CenterResponse()
 148
 149 if __name__ == "__main__":
 150         rospy.init_node('DWM1000')
 151         dwleft  = DW1000("uwb_dist_left",  0xc2, +0.02)
 152         dwright = DW1000("uwb_dist_right", 0xc0, -0.02)
 153         dist_l_r = 0.285
 154         rate = rospy.Rate(10)
 155         pos = Position()
 156         tf_broadcaster = tf.broadcaster.TransformBroadcaster()
 157         rospy.Service('/DWM1000/center', DWM1000Center, handle_center_call)
 158
 159         while not rospy.is_shutdown() and dwleft.is_alive() and dwright.is_alive():
 160                 dist_left = dwleft.distance_valid()
 161                 dist_right = dwright.distance_valid()
 162                 if dist_left == None or dist_right == None:
 163                         print "no valid sensor update"
 164                         # run kalman prediction only
 165                         pos.filter(None, None)
 166                 else:
 167                         dir = "left" if (dist_left < dist_right) else "right"
 168
 169                         diff = abs(dist_left - dist_right)
 170                         if diff >= dist_l_r:
 171                                 # difference to high, correct to maximum
 172                                 off = diff - dist_l_r + 0.01
 173                                 if dist_left > dist_right:
 174                                         dist_left -= off/2
 175                                         dist_right += off/2
 176                                 else:
 177                                         dist_left += off/2
 178                                         dist_right -= off/2
 179                         print "%.2f %.2f %.2f %.2f %s" % (dwleft.distance(), dwright.distance(), dist_left, dist_right, dir)
 180
 181                         a_r = (-dist_right**2 + dist_left**2 - dist_l_r**2) / (-2*dist_l_r)
 182                         x = dist_l_r/2 - a_r
 183                         t = dist_right**2 - a_r**2
 184                         if t >= 0:
 185                                 y = sqrt(t)
 186                                 print x,y
 187                                 # Rotate 90 deg
 188                                 x, y = (y, -x)
 189
 190                                 x, y = pos.filter(x, y)
 191                                 tf_broadcaster.sendTransform((x, y, 0.0), (0, 0, 0, 1), rospy.Time.now(), "uwb_beacon", "base_footprint")
 192
 193                                 if VISULAIZE:
 194                                         circle_left = plt.Circle((-dist_l_r/2, 0), dwleft.distance, color='red', fill=False)
 195                                         circle_right = plt.Circle((dist_l_r/2, 0), dwright.distance, color='green', fill=False)
 196                                         plt.gca().add_patch(circle_left)
 197                                         plt.gca().add_patch(circle_right)
 198                                         plt.grid(True)
 199                                         plt.axis('scaled')
 200                                         plt.show()
 201                         else:
 202                                 # No current position, still need up update kalman prediction
 203                                 pos.filter(None, None)
 204
 205                 rate.sleep()