--- /dev/null
+<?xml version="1.0"?>
+
+<!-- Launch file for ekf_localization_node -->
+<launch>
+
+ <!-- This node will take in measurements from odometry, IMU, stamped pose, and stamped twist messages. It tracks
+ the state of the robot, with the state vector being defined as X position, Y position, Z position,
+ roll, pitch, yaw, their respective velocites, and linear acceleration. Units for all measurements are assumed
+ to conform to the SI standard as specified in REP-103. -->
+ <node pkg="robot_localization" type="ekf_localization_node" name="ekf_localization" clear_params="true" output="screen">
+
+ <!-- ======== STANDARD PARAMETERS ======== -->
+
+ <!-- The frequency, in Hz, at which the filter will output a position estimate. Note that
+ the filter will not begin computation until it receives at least one message from
+ one of the inputs. It will then run continuously at the frequency specified here,
+ regardless of whether it receives more measurements. Defaults to 30 if unspecified. -->
+ <param name="frequency" value="20"/>
+
+ <!-- The period, in seconds, after which we consider a sensor to have timed out. In this event, we
+ carry out a predict cycle on the EKF without correcting it. This parameter can be thought of
+ as the minimum frequency with which the filter will generate new output. Defaults to 1 / frequency
+ if not specified. -->
+ <param name="sensor_timeout" value="2.0"/>
+
+ <!-- If this is set to true, no 3D information will be used in your state estimate. Use this if you
+ are operating in a planar environment and want to ignore the effect of small variations in the
+ ground plane that might otherwise be detected by, for example, an IMU. Defaults to false if
+ unspecified. -->
+ <param name="two_d_mode" value="true"/>
+
+ <!-- REP-105 (http://www.ros.org/reps/rep-0105.html) specifies three principal coordinate frames: map,
+ odom, and base_link. base_link is the coordinate frame that is affixed to the robot. The robot's
+ position in the odom frame will drift over time, but is accurate in the short term and should be
+ continuous. The odom frame is therefore the best frame for executing local motion plans. The map
+ frame, like the odom frame, is a world-fixed coordinate frame, and while it contains the most
+ globally accurate position estimate for your robot, it is subject to discrete jumps, e.g., due to
+ the fusion of GPS data. Here is how to use the following settings:
+ 1. Set the map_frame, odom_frame, and base_link frames to the appropriate frame names for your system.
+ * If your system does not have a map_frame, just remove it, and make sure "world_frame" is set
+ to the value of odom_frame.
+ 2. If you are fusing continuous position data such as wheel encoder odometry, visual odometry, or IMU data,
+ set "world_frame" to your odom_frame value. This is the default behavior for robot_localization's state
+ estimation nodes.
+ 3. If you are fusing global absolute position data that is subject to discrete jumps (e.g., GPS or position
+ updates from landmark observations) then:
+ 3a. Set your "world_frame" to your map_frame value
+ 3b. MAKE SURE something else is generating the odom->base_link transform. Note that this can even be
+ another instance of robot_localization! However, that instance should *not* fuse the global data. -->
+ <!-- Defaults to "map" if unspecified -->
+ <param name="map_frame" value="map"/>
+ <!-- Defaults to "odom" if unspecified -->
+ <param name="odom_frame" value="odom"/>
+ <!-- Defaults to "base_link" if unspecified -->
+ <param name="base_link_frame" value="base_footprint"/>
+ <!-- Defaults to the value of "odom_frame" if unspecified -->
+ <param name="world_frame" value="odom"/>
+
+ <!-- Use this parameter to provide an offset to the transform generated by ekf_localization_node. This
+ can be used for future dating the transform, which is required for interaction with some other
+ packages. Defaults to 0.0 if unspecified. -->
+ <param name="transform_time_offset" value="0.0"/>
+
+ <!-- The filter accepts an arbitrary number of inputs from each input message type (Odometry, PoseStamped,
+ TwistStamped, Imu). To add a new one, simply append the next number in the sequence to its base name,
+ e.g., odom0, odom1, twist0, twist1, imu0, imu1, imu2, etc. The value should be the topic name. These
+ parameters obviously have no default values, and must be specified. -->
+ <param name="odom0" value="odom"/>
+ <param name="imu0" value="imu"/>
+ <param name="odom1" value="gps"/>
+
+ <!-- Each sensor reading updates some or all of the filter's state. These options give you greater control over
+ which values from each measurement are fed to the filter. For example, if you have an odometry message as input,
+ but only want to use its Z position value, then set the entire vector to false, except for the third entry.
+ The order of the values is x, y, z, roll, pitch, yaw, vx, vy, vz, vroll, vpitch, vyaw, ax, ay, az. Note that not some
+ message types lack certain variables. For example, a TwistWithCovarianceStamped message has no pose information, so
+ the first six values would be meaningless in that case. Each vector defaults to all false if unspecified, effectively
+ making this parameter required for each sensor. -->
+ <rosparam param="odom0_config">[true, true, false, false, false, true, true, true, false, false, false, true, true, true, false]</rosparam>
+ <rosparam param="imu0_config">[false, false, false, true, true, true, false, false, false, true, true, true, true, true, true]</rosparam>
+ <rosparam param="odom1_config">[true, true, true, false, false, false, true, true, true, false, false, false, true, true, true]</rosparam>
+
+
+ <!-- The best practice for including new sensors in robot_localization's state estimation nodes is to pass in velocity
+ measurements and let the nodes integrate them. However, this isn't always feasible, and so the state estimation
+ nodes support fusion of absolute measurements. If you have more than one sensor providing absolute measurements,
+ however, you may run into problems if your covariances are not large enough, as the sensors will inevitably
+ diverge from one another, causing the filter to jump back and forth rapidly. To combat this situation, you can
+ either increase the covariances for the variables in question, or you can simply set the sensor's differential
+ parameter to true. When differential mode is enabled, all absolute pose data is converted to velocity data by
+ differentiating the absolute pose measurements. These velocities are then integrated as usual. NOTE: this only
+ applies to sensors that provide absolute measurements, so setting differential to true for twit measurements has
+ no effect.
+
+ Users should take care when setting this to true for orientation variables: if you have only one source of
+ absolute orientation data, you should not set the differential parameter to true. This is due to the fact that
+ integration of velocities leads to slowly increasing error in the absolute (pose) variable. For position variables,
+ this is acceptable. For orientation variables, it can lead to trouble. Users should make sure that all orientation
+ variables have at least one source of absolute measurement. -->
+ <param name="odom0_differential" value="true"/>
+ <param name="imu0_differential" value="false"/>
+ <param name="odom1_differential" value="true"/>
+
+ <!-- When the node starts, if this parameter is true, then the first measurement is treated as a "zero point" for all
+ future measurements. While you can achieve the same effect with the differential paremeter, the key difference is
+ that the relative parameter doesn't cause the measurement to be converted to a velocity before integrating it. If
+ you simply want your measurements to start at 0 for a given sensor, set this to true. -->
+ <param name="odom0_relative" value="false"/>
+ <param name="imu0_relative" value="false"/>
+ <param name="odom1_relative" value="false"/>
+
+ <!-- If we're including accelerations in our state estimate, then we'll probably want to remove any acceleration that
+ is due to gravity for each IMU. If you don't want to, then set this to false. Defaults to false if unspecified. -->
+ <param name="imu0_remove_gravitational_acceleration" value="true"/>
+
+ <!-- If you're having trouble, try setting this to true, and then echo the /diagnostics_agg topic to see
+ if the node is unhappy with any settings or data. -->
+ <param name="print_diagnostics" value="true"/>
+
+ <remap from="odometry/filtered" to="odom_combined"/>
+
+ </node>
+
+</launch>
--- /dev/null
+#!/usr/bin/env python
+# -*- coding: iso-8859-15 -*-
+
+import rospy
+import tf
+import actionlib
+from math import *
+from move_base_msgs.msg import MoveBaseAction, MoveBaseGoal
+from actionlib_msgs.msg import GoalStatus
+from optparse import OptionParser
+
+
+class Square:
+ def __init__(self):
+ rospy.init_node('umbmark')
+ self.move_base = actionlib.SimpleActionClient("move_base", MoveBaseAction)
+ while not self.move_base.wait_for_server(rospy.Duration(5)):
+ rospy.loginfo("Waiting for the move_base action server to come up")
+
+ def next_pos(self, x, y, angle):
+ odom_quat = tf.transformations.quaternion_from_euler(0, 0, angle)
+
+ rospy.loginfo("Moving to (%.2f, %2f), %d°.." % (x, y, angle*180/pi))
+
+ goal = MoveBaseGoal()
+ goal.target_pose.header.frame_id = "odom"
+ goal.target_pose.header.stamp = rospy.Time.now()
+ goal.target_pose.pose.position.x = x
+ goal.target_pose.pose.position.y = y
+ goal.target_pose.pose.orientation.x = odom_quat[0]
+ goal.target_pose.pose.orientation.y = odom_quat[1]
+ goal.target_pose.pose.orientation.z = odom_quat[2]
+ goal.target_pose.pose.orientation.w = odom_quat[3]
+ self.move_base.send_goal(goal)
+
+ self.move_base.wait_for_result()
+
+ if self.move_base.get_state() == GoalStatus.SUCCEEDED:
+ rospy.loginfo("The base moved to (%.2f, %2f), %d°" % (x, y, angle*180/pi))
+ else:
+ rospy.logerr("The base failed to (%.2f, %2f), %d°" % (x, y, angle*180/pi))
+ raise
+
+ def run(self, size=1):
+ self.next_pos(0, 0, 0)
+ self.next_pos(size, 0, 0)
+ self.next_pos(size, -size, 0)
+ self.next_pos(0, size, 0)
+
+if __name__ == "__main__":
+ parser = OptionParser()
+ parser.add_option("-l", "--length", dest="length", default=2, help="Square size")
+ (options, args) = parser.parse_args()
+
+ p = Square()
+ p.run(float(options.length))
import rospy
import tf
import struct
+import prctl
from i2c import *
from math import *
from geometry_msgs.msg import Twist
class MoveBase:
def __init__(self):
rospy.init_node('wild_thumper')
- rospy.Subscriber("cmd_vel", Twist, self.cmdVelReceived)
+ prctl.set_name("wild_thumper")
+ rospy.Subscriber("cmd_vel_out", Twist, self.cmdVelReceived)
rospy.Subscriber("imu", Imu, self.imuReceived)
enable_odom_tf = rospy.get_param("~enable_odom_tf", True)
if enable_odom_tf:
self.get_voltage()
if i % 2:
self.get_dist_forward()
- self.get_dist_backward()
self.get_dist_left()
+ else:
+ self.get_dist_backward()
self.get_dist_right()
i+=1
rate.sleep()
val = struct.unpack(">H", s)[0]
return val
- def get_dist_srf(self, num):
+ def start_dist_srf(self, num):
dev = i2c(0x52)
s = struct.pack("B", num)
dev.write(s)
dev.close()
- sleep(50e-3)
+ def read_dist_srf(self, num):
+ dev = i2c(0x52)
+ s = struct.pack("B", num)
+ dev.write(s)
+ dev.close()
dev = i2c(0x52)
s = dev.read(2)
def get_dist_left(self):
if self.pub_range_left.get_num_connections() > 0:
dist = 30.553/(self.get_dist_ir(0x1) - -67.534)
- self.send_range(self.pub_range_left, "ir_left", Range.INFRARED, dist, 0.04, 0.3, 5)
+ self.send_range(self.pub_range_left, "ir_left", Range.INFRARED, dist, 0.04, 0.3, 1)
def get_dist_right(self):
if self.pub_range_right.get_num_connections() > 0:
dist = 17.4/(self.get_dist_ir(0x3) - 69)
- self.send_range(self.pub_range_right, "ir_right", Range.INFRARED, dist, 0.04, 0.3, 5)
+ self.send_range(self.pub_range_right, "ir_right", Range.INFRARED, dist, 0.04, 0.3, 1)
def get_dist_forward(self):
if self.pub_range_fwd.get_num_connections() > 0:
- dist = self.get_dist_srf(0x5)
+ dist = self.read_dist_srf(0x15)
self.send_range(self.pub_range_fwd, "sonar_forward", Range.ULTRASOUND, dist, 0.04, 6, 30)
+ self.start_dist_srf(0x5) # get next value
def get_dist_backward(self):
if self.pub_range_bwd.get_num_connections() > 0:
- dist = self.get_dist_srf(0x7)
+ dist = self.read_dist_srf(0x17)
self.send_range(self.pub_range_bwd, "sonar_backward", Range.ULTRASOUND, dist, 0.04, 6, 30)
+ self.start_dist_srf(0x7) # get next value
if __name__ == "__main__":