# Output of robot_pose_ekf jumps uncontrollably [closed]

I would like to fuse data from a magnetometer, wheel odometry and a GPS sensor using the robot_pose_ekf. Since I would like to take advantage of the fact that both magnetometer and GPS are defined within an absolute reference frame, I switched to a fork by clearpath robotics which is publicly available.

I publish my wheel odometry on topic /odom:

```
dat = tf.transformations.quaternion_from_euler(0, 0,self.th)
quaternion = Quaternion(dat[0],dat[1],dat[2],dat[3])
odom = Odometry()
odom.header.stamp = now
odom.header.frame_id = "odom_combined"
odom.pose.pose.position.x = self.x
odom.pose.pose.position.y = self.y
odom.pose.pose.position.z = 0
odom.pose.pose.orientation = quaternion
odom.pose.covariance= [0.000001, 0, 0, 0, 0, 0,
0, 0.000001, 0, 0, 0, 0,
0, 0, 0.000001, 0, 0, 0,
0, 0, 0, 0.000001, 0, 0,
0, 0, 0, 0, 0.000001, 0,
0, 0, 0, 0, 0, 0.000001]
odom.twist.covariance = [99999, 0, 0, 0, 0, 0,
0, 99999, 0, 0, 0, 0,
0, 0, 99999, 0, 0, 0,
0, 0, 0, 99999, 0, 0,
0, 0, 0, 0, 99999, 0,
0, 0, 0, 0, 0, 99999]
odom.child_frame_id = "base_footprint"
self.odomPub.publish(odom)
```

My gps in topic /gps

```
odom = Odometry()
odom.header.stamp = rospy.Time.now()
odom.header.frame_id = "odom_combined"
(x, y) = self.converter.LatLong2UTM(self.lat, self.lon)
odom.pose.pose.position.x = x
odom.pose.pose.position.y = y
odom.pose.pose.position.z = 0
dat = tf.transformations.quaternion_from_euler(0, 0, 0)
odom.pose.pose.orientation = Quaternion(dat[0],dat[1],dat[2],dat[3])
odom.child_frame_id = "base_footprint"
odom.pose.covariance =[1, 0, 0, 0, 0, 0, # covariance on gps_x
0, 1, 0, 0, 0, 0, # covariance on gps_y
0, 0, 1, 0, 0, 0, # covariance on gps_z
0, 0, 0, 99999, 0, 0, # large covariance on rot x
0, 0, 0, 0, 99999, 0, # large covariance on rot y
0, 0, 0, 0, 0, 99999] # large covariance on rot z
odom.twist.covariance = [99999, 0, 0, 0, 0, 0,
0, 99999, 0, 0, 0, 0,
0, 0, 99999, 0, 0, 0,
0, 0, 0, 99999, 0, 0,
0, 0, 0, 0, 99999, 0,
0, 0, 0, 0, 0, 99999]
self.pub.publish(odom)
```

and my compass data in /imu_data

```
im = Imu()
ori = tf.transformations.quaternion_from_euler(0, 0, math.radians(bearing))
qua = Quaternion(ori[0],ori[1],ori[2],ori[3])
im.header.frame_id = "imu_data"
im.header.stamp = rospy.Time.now()
im.orientation = qua
im.orientation_covariance = [0.000001, 0, 0,
0, 0.000001, 0,
0, 0, 0.000001]
# Switch others off for now.
im.angular_velocity_covariance = [99999, 0, 0,
0, 99999, 0,
0, 0, 99999]
im.linear_acceleration_covariance = [99999, 0, 0,
0, 99999, 0,
0, 0, 99999]
self.imupub.publish(im)
```

I've been toying around with the covariance values a lot, but they don't seem to have any influence on my particular problem..

Furthermore, I've had problems with robot_pose_ekf giving me transformation errors, even when I ...