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August 8, 2021 03:50
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#!/usr/bin/env python | |
#ROS Node to convert a GPS waypoint published on the topic "waypoint" into a 2D Navigation Goal in SLAM to achieve autonomous navigation to a GPS Waypoint | |
#Converts Decimal GPS Coordinates of waypoint to ROS Position Vector relative to the current gps position of the robot | |
#Accounts for curvature of the earth using haversine formula | |
#Depends rospy, std_msgs, geographic_msgs, sensor_msgs, numpy | |
#Written by Alex McClung, 2015, [email protected], To be Released Open Source under Creative Commons Attribution Share-Alike Licence | |
import roslib | |
import rospy | |
from math import radians, cos, sin, asin, sqrt, pow, pi, atan2 | |
import numpy as np | |
from std_msgs.msg import String | |
from sensor_msgs.msg import NavSatFix | |
from geometry_msgs.msg import PoseStamped | |
from geometry_msgs.msg import PoseWithCovarianceStamped | |
from geographic_msgs.msg import WayPoint | |
debug = False | |
latCur = 0.0 | |
lonCur = 0.0 | |
latWP = 0.0 | |
lonWP = 0.0 | |
altWP = 0.0 | |
earthRadius = 6371000.0 #Metres | |
currPosX = 0.0 | |
currPosY = 0.0 | |
currPosZ = 0.0 | |
WPUpdateState = False #True if there has been an update in the waypoint position | |
lastValidFixTime = 0.0 | |
gpsValidityTimeout = 10.0 #Seconds | |
def haversineDistance(latCur, lonCur, latWP, lonWP): #Returns distance to waypoint in Metres | |
latWP, lonWP, latCur, lonCur = map(radians, [latWP, lonWP, latCur, lonCur]) #Convert into Radians to perform math | |
a = pow(sin((latWP - latCur)/2),2) + cos(latCur) * cos(latWP) * pow(sin((lonWP - lonCur)/2),2) | |
return earthRadius * 2.0 * asin(sqrt(a)) #Return calculated distance to waypoint in Metres | |
def bearing(latCur, lonCur, latWP, lonWP): #Bearing to waypoint (degrees) | |
latWP, lonWP, latCur, lonCur = map(radians, [latWP, lonWP, latCur, lonCur]) #Convert into Radians to perform math | |
dLon = lonWP - lonCur | |
return atan2(sin(dLon) * cos(latWP), cos(latCur) * sin(latWP) - (sin(latCur) * cos(latWP) * cos(dLon))) | |
def gpsSubscriber(gpsMsg): #GPS Coordinate recieved from ROS topic, run this function | |
if gpsMsg.status.status > -1: #If there is a GPS fix (Either Augmented or Unaugmented) | |
global latCur | |
global lonCur | |
global lastValidFixTime | |
lastValidFixTime = rospy.get_time() | |
latCur = gpsMsg.latitude | |
lonCur = gpsMsg.longitude | |
if debug == True: | |
rospy.loginfo("GPS Fix Available, Latitude: %f, Longitude: %f", latCur, lonCur) | |
def gpsFixIsValid(): #Check to see if there has been a GPS fix within the last <gpsValidityTimeout> seconds | |
global gpsValidityTimeout | |
if (rospy.get_time()- lastValidFixTime) < gpsValidityTimeout: | |
return True | |
else: | |
rospy.loginfo("GPS Fix Invalid! Last valid update was: %f seconds ago", rospy.get_time()- lastValidFixTime) | |
return False | |
def robotPoseSubscriber(poseMsg): #Odometry update recieved from ROS topic, run this function | |
global currPosX | |
global currPosY | |
global currPosZ | |
currPosX = poseMsg.pose.pose.position.x | |
currPosY = poseMsg.pose.pose.position.y | |
currPosZ = poseMsg.pose.pose.position.z | |
def waypointSubscriber(WPMsg): #Waypoint Command recieved from ROS topic, run this function | |
global waypointUpdateState | |
global latWP | |
global lonWP | |
global altWP | |
WPUpdateState = True | |
latWP = WPMsg.position.latitude | |
lonWP = WPMsg.position.longitude | |
altWP = WPMsg.position.altitude | |
rospy.loginfo("Recieved Waypoint Command, Latitude: %f, Longitude: %f", latWP, lonWP) | |
if gpsFixIsValid() == True: #If there is a valid GPS fix, publish nav goal to ROS | |
posePublisher() | |
def posePublisher(): #Convert absolute waypoint to vector relative to robot, then publish navigation goal to ROS | |
desiredPose = PoseStamped() | |
desiredPose.header.frame_id = "/gps_link" | |
desiredPose.header.stamp = rospy.Time.now() | |
global currPosX | |
global currPosY | |
global currPosZ | |
global debug | |
if debug: | |
rospy.loginfo("LatWP: %f, LonWP: %f, LatCur: %f, LonCur: %f", latWP, lonWP, latCur, lonCur) | |
distToWP = haversineDistance(latCur, lonCur, latWP, lonWP) | |
bearingToWP = bearing(latCur, lonCur, latWP, lonWP) | |
desiredPose.pose.position.x = currPosX + (distToWP * cos(bearingToWP)) #Convert distance and angle to waypoint from Polar to Cartesian co-ordinates then add current position of robot odometry | |
desiredPose.pose.position.y = currPosY + (distToWP * sin(bearingToWP)) | |
desiredPose.pose.position.z = altWP - currPosZ #Assuming CurrPosZ is abslolute (eg barometer or GPS) | |
desiredPose.pose.orientation.x = 0 | |
desiredPose.pose.orientation.y = 0 | |
desiredPose.pose.orientation.z = 0 | |
desiredPose.pose.orientation.w = 1 | |
navGoalPub = rospy.Publisher('move_base_simple/goal', PoseStamped, queue_size=10) #Publish Nav Goal to ROS topic | |
navGoalPub.publish(desiredPose) | |
rospy.loginfo("GPS Fix is Valid! Setting Navigation Goal to: %f, %f, %f", desiredPose.pose.position.x, desiredPose.pose.position.y, desiredPose.pose.position.z) | |
rospy.loginfo("Robot is heading %f metres at a bearing of %f degrees", distToWP, (bearingToWP * 180/pi + 360) % 360) | |
def main(): | |
rospy.init_node('gps_2d_nav_goal', anonymous=True) | |
rospy.loginfo("Initiating GPS 2D Nav Goal Node.") | |
while not rospy.is_shutdown(): #While ros comms are running smoothly | |
rospy.Subscriber("waypoint", WayPoint, waypointSubscriber) #Subscribe to "pose", "fix" and "waypoint" ROS topics | |
rospy.Subscriber("fix", NavSatFix, gpsSubscriber) | |
rospy.Subscriber("odom_combined", PoseWithCovarianceStamped, robotPoseSubscriber) | |
rospy.spin() | |
if __name__ == '__main__': | |
try: | |
main() | |
except rospy.ROSInterruptException: | |
pass |
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Hi,
I have one question. what is the role of desiredPose.pose.position.x? what does it show ?
Now i am using odometry information published from SLAM, and give it as an input to this python code. now i want to compare the results between when i donot have any odometry information with the time that I have merged odometry information with the gps information.
from which result i can make a conclusion? and identify that for instance using odometry information make the result better or not
and also i want to know what is the impact of using odometry information, with the time that we donot ues it
Thanks in advance