#!/usr/bin/env python3
'''
logdemo.py : BreezySLAM Python demo. Reads logfile with odometry and scan data
from Paris Mines Tech and displays showing robot pose and map in
real time.
For details see
@inproceedings{coreslam-2010,
author = {Bruno Steux and Oussama El Hamzaoui},
title = {CoreSLAM: a SLAM Algorithm in less than 200 lines of C code},
booktitle = {11th International Conference on Control, Automation,
Robotics and Vision, ICARCV 2010, Singapore, 7-10
December 2010, Proceedings},
pages = {1975-1979},
publisher = {IEEE},
year = {2010}
}
Copyright (C) 2016 Simon D. Levy and Matt Lubas
This code is free software: you can redistribute it and/or modify
it under the terms of the GNU Lesser General Public License as
published by the Free Software Foundation, either version 3 of the
License, or (at your option) any later version.
This code is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU Lesser General Public License
along with this code. If not, see .
'''
# Map size, scale
MAP_SIZE_PIXELS = 800
MAP_SIZE_METERS = 32
from breezyslam.algorithms import Deterministic_SLAM, RMHC_SLAM
from mines import MinesLaser, Rover, load_data
from pltslamshow import SlamShow
from sys import argv, exit
from time import sleep
from threading import Thread
import pickle
def threadfunc(robot, slam, timestamps, lidars, odometries, mapbytes, pose):
'''
Threaded function runs SLAM, setting the map bytes and robot pose for display
on the main thread.
'''
# Initialize time for delay
prevtime = 0
# Loop over scans
for scanno in range(len(lidars)):
if odometries is None:
# Update SLAM with lidar alone
slam.update(lidars[scanno])
else:
# Convert odometry to velocities
velocities = robot.computePoseChange(odometries[scanno])
# Update SLAM with lidar and velocities
slam.update(lidars[scanno], velocities)
# Get new position
pose[0],pose[1],pose[2] = slam.getpos()
# Get new map
slam.getmap(mapbytes)
# Add delay to yield to main thread
currtime = timestamps[scanno] / 1.e6 # Convert usec to sec
if prevtime > 0:
sleep(currtime-prevtime)
prevtime = currtime
def main():
# Bozo filter for input args
if len(argv) < 4:
print('Usage: %s [random_seed]' % argv[0])
print('Example: %s exp2 1 9999' % argv[0])
exit(1)
# Grab input args
dataset = argv[1]
use_odometry = True if int(argv[2]) else False
seed = int(argv[3]) if len(argv) > 3 else 0
# Allocate byte array to receive map updates
mapbytes = bytearray(MAP_SIZE_PIXELS * MAP_SIZE_PIXELS)
# Load the data from the file
timestamps, lidars, odometries = load_data('.', dataset)
# Build a robot model if we want odometry
robot = Rover() if use_odometry else None
# Create a CoreSLAM object with laser params and optional robot object
slam = RMHC_SLAM(MinesLaser(), MAP_SIZE_PIXELS, MAP_SIZE_METERS, random_seed=seed) \
if seed \
else Deterministic_SLAM(MinesLaser(), MAP_SIZE_PIXELS, MAP_SIZE_METERS)
# Set up a SLAM display, named by dataset
display = SlamShow(MAP_SIZE_PIXELS, MAP_SIZE_METERS*1000/MAP_SIZE_PIXELS, dataset)
# Pose will be modified in our threaded code
pose = [0,0,0]
# Launch the data-collection / update thread
thread = Thread(target=threadfunc, args=(robot, slam, timestamps, lidars, odometries if use_odometry else None, mapbytes, pose))
thread.daemon = True
thread.start()
# Loop forever,displaying current map and pose
while True:
# Display map and robot pose
display.displayMap(mapbytes)
display.setPose(*pose)
# Refresh the display, exiting gracefully if user closes it
if not display.refresh():
exit(0)
main()