dwm1000: Always send transform even if there are no valid sensors values

[ros_wild_thumper.git] / scripts / dwm1000.py

diff --git a/scripts/dwm1000.py b/scripts/dwm1000.py
index bf58657c90a129dbe9579f7475f9b2db9af91a64..707dff19f05e75865b6371b789daf84a1159db86 100755 (executable)
--- a/scripts/dwm1000.py
+++ b/scripts/dwm1000.py
@@ -42,6 +42,10 @@ class simple_kalman:
 
                return x
 
+       def set_measure_cov(self, R):
+               if R > 0:
+                       self.R = R
+
 class DW1000(threading.Thread):
        def __init__(self, name, addr, offset):
                threading.Thread.__init__(self)
@@ -73,10 +77,10 @@ class DW1000(threading.Thread):
 
        def run(self):
                last_val = 10
-               while True:
+               while not rospy.is_shutdown():
                        val = self.get_value()
-                       if abs(val - last_val)  > 10:
-                               print "Ignoring values too far apart %s: %.2f - %.2f" % (self.name, val, last_val)
+                       if abs(val - last_val)  > 50:
+                               rospy.logwarn("Ignoring values too far apart %s: %.2f - %.2f", self.name, val, last_val)
                        elif not isnan(val):
                                self.dist = val + self.offset
                                self.last_update = datetime.now()
@@ -93,9 +97,12 @@ class Position:
                P_est_x = 0.02
                P_est_y = 0.01
                # Systemrauschen
-               Q = 0.002
-               self.filter_x = simple_kalman(1.0, P_est_x, Q, Rx)
-               self.filter_y = simple_kalman(0.0, P_est_y, Q, Ry)
+               Qx = 0.001
+               Qy = 0.00001
+               # TODO: Replace 2x 1d kalman with 2d kalman
+               # so the polyfit variance can be replaced with a covariance matrix
+               self.filter_x = simple_kalman(1.0, P_est_x, Qx, Rx)
+               self.filter_y = simple_kalman(0.0, P_est_y, Qy, Ry)
                self.speed_x = 0
                self.speed_y = 0
                self.speed_z = 0
@@ -107,10 +114,6 @@ class Position:
                self.speed_y = msg.twist.twist.linear.y
                self.speed_z = msg.twist.twist.angular.z
 
-       """
-       TODO:
-       - variance of kalman should be dependant on distance
-       """
        def filter(self, x, y):
                # Correct estimation with speed
                current_time = rospy.Time.now()
@@ -131,6 +134,11 @@ class Position:
                if x != None and y != None:
                        x = self.filter_x.run(x)
                        y = self.filter_y.run(y)
+
+                       # Update variance
+                       dist = np.linalg.norm([x, y])
+                       self.filter_x.set_measure_cov(np.polyval([0.018, 0.0, 0.0], dist))
+                       self.filter_y.set_measure_cov(np.polyval([0.006, 0.0, 0.0], dist))
                else:
                        x = self.filter_x.x_est
                        y = self.filter_y.x_est
@@ -143,14 +151,14 @@ def handle_center_call(req):
        diff = dwleft.distance_valid() - dwright.distance_valid()
        dwleft.offset -= diff/2
        dwright.offset += diff/2
-       print "Centering to %.2f %.2f" % (dwleft.offset, dwright.offset)
+       rospy.loginfo("Centering to %.2f %.2f", dwleft.offset, dwright.offset)
        return DWM1000CenterResponse()
 
 if __name__ == "__main__":
-       rospy.init_node('DWM1000')
-       dwleft  = DW1000("uwb_dist_left",  0xc2, +0.02)
-       dwright = DW1000("uwb_dist_right", 0xc0, -0.02)
-       dist_l_r = 0.285
+       rospy.init_node('DWM1000', log_level=rospy.DEBUG)
+       dwleft  = DW1000("uwb_dist_left",  0xc2, +0.0)
+       dwright = DW1000("uwb_dist_right", 0xc0, -0.0)
+       dist_l_r = 0.285 # Distance between both DWM1000
        rate = rospy.Rate(10)
        pos = Position()
        tf_broadcaster = tf.broadcaster.TransformBroadcaster()
@@ -159,10 +167,12 @@ if __name__ == "__main__":
        while not rospy.is_shutdown() and dwleft.is_alive() and dwright.is_alive():
                dist_left = dwleft.distance_valid()
                dist_right = dwright.distance_valid()
+               x = None
+               y = None
                if dist_left == None or dist_right == None:
-                       print "no valid sensor update"
+                       rospy.logerr_throttle(10, "no valid sensor update %r %r" % (dist_left, dist_right))
                        # run kalman prediction only
-                       pos.filter(None, None)
+                       x,y = pos.filter(None, None)
                else:
                        dir = "left" if (dist_left < dist_right) else "right"
 
@@ -176,19 +186,18 @@ if __name__ == "__main__":
                                else:
                                        dist_left += off/2
                                        dist_right -= off/2
-                       print "%.2f %.2f %.2f %.2f %s" % (dwleft.distance(), dwright.distance(), dist_left, dist_right, dir)
+                       rospy.logdebug("%.2f %.2f %.2f %.2f %s", dwleft.distance(), dwright.distance(), dist_left, dist_right, dir)
 
                        a_r = (-dist_right**2 + dist_left**2 - dist_l_r**2) / (-2*dist_l_r)
                        x = dist_l_r/2 - a_r
                        t = dist_right**2 - a_r**2
                        if t >= 0:
                                y = sqrt(t)
-                               print x,y
+                               rospy.logdebug("x=%.2f, y=%.2f", x, y)
                                # Rotate 90 deg
                                x, y = (y, -x)
 
                                x, y = pos.filter(x, y)
-                               tf_broadcaster.sendTransform((x, y, 0.0), (0, 0, 0, 1), rospy.Time.now(), "uwb_beacon", "base_footprint")
 
                                if VISULAIZE:
                                        circle_left = plt.Circle((-dist_l_r/2, 0), dwleft.distance, color='red', fill=False)
@@ -200,6 +209,7 @@ if __name__ == "__main__":
                                        plt.show()
                        else:
                                # No current position, still need up update kalman prediction
-                               pos.filter(None, None)
+                               x, y = pos.filter(None, None)
+               tf_broadcaster.sendTransform((x, y, 0.0), (0, 0, 0, 1), rospy.Time.now(), "uwb_beacon", "base_footprint")
 
                rate.sleep()