breezyslam建图2d-slam建图测试一

lidar 2020-5-23 10746 2

这篇文章是基于breezyslam 建图的后续，对breezyslam的建图进行测试，

使用树莓派3B+思兰激光雷达，

使用Python的所有库，所有库的安装和记录请查看这篇文章

教程四：树莓派搭建breezyslam环境的说明

http://blog.cvosrobot.com/?post=486

笔者编写了下面的脚本

#!/usr/bin/env python3

'''
rpslam_vos.py : BreezySLAM Python with SLAMTECH RP A1 Lidar

Copyright (C) 2018 Simon D. Levy

You should have received a copy of the GNU Lesser General Public License 
along with this code.  If not, see <http://www.gnu.org/licenses/>.
'''

MAP_SIZE_PIXELS         = 500
MAP_SIZE_METERS         = 10
LIDAR_DEVICE            = '/dev/rplidar'

# Ideally we could use all 250 or so samples that the RPLidar delivers in one 
# scan, but on slower computers you'll get an empty map and unchanging position
# at that rate.
MIN_SAMPLES   = 180

import sys
import os
import time
from breezyslam.algorithms import RMHC_SLAM
from breezyslam.sensors import RPLidarA1 as LaserModel
from rplidar import RPLidar as Lidar
from roboviz import MapVisualizer
from rplidar import  RPLidarException

if __name__ == '__main__':

    # Connect to Lidar unit  until lidar is normal 

    berror = True
    while berror == True:
        lidar = Lidar(LIDAR_DEVICE)
        try:
            info = lidar.get_info()
            berror = False
        except RPLidarException as err:
            print(err)
            time.sleep(1)
            berror = True
            lidar.stop()
            lidar.disconnect()
            pass

    # print lidar information 
    print(info)
    #print lidar health status
    health = lidar.get_health() 
    print("health status:")    
    print(health)

    # Create an RMHC SLAM object with a laser model and optional robot model
    slam = RMHC_SLAM(LaserModel(), MAP_SIZE_PIXELS, MAP_SIZE_METERS)

    # Set up a SLAM display
    viz = MapVisualizer(MAP_SIZE_PIXELS, MAP_SIZE_METERS, 'VosSLAM')

    # Initialize an empty trajectory
    trajectory = []

    # Initialize empty map
    mapbytes = bytearray(MAP_SIZE_PIXELS * MAP_SIZE_PIXELS)

    # Create an iterator to collect scan data from the RPLidar
 #   iterator = lidar.iter_scans()

    # We will use these to store previous scan in case current scan is inadequate
    previous_distances = None
    previous_angles    = None

    # First scan is crap, so ignore it
  #  next(iterator)

    while True:
        for i,scan in enumerate(lidar.iter_scans()):
            print('%d: Got %d measurments' % (i, len(scan)))
            if i > 0:
                distances = [item[2] for item in scan]
                angles    = [item[1] for item in scan]
                # Update SLAM with current Lidar scan and scan angles if adequate
                slam.update(distances, scan_angles_degrees=angles)

                # Get current robot position
                x, y, theta = slam.getpos()

                # Get current map bytes as grayscale
                slam.getmap(mapbytes)
                     # Display map and robot pose, exiting gracefully if user closes it
                if not viz.display(x/1000., y/1000., theta, mapbytes):
                 exit(0)
                # Extract distances and angles from triples

    # Shut down the lidar connection
    lidar.stop()
    lidar.disconnect()

 python3 rpslam_vos.py 
Incorrect descriptor starting bytes
{'model': 24, 'hardware': 0, 'firmware': (1, 18), 'serialnumber': '5CB4FBF2C8E49CCFC6E49FF1A266530D'}
health status:
('Good', 0)
0: Got 140 measurments
1: Got 210 measurments
2: Got 208 measurments
3: Got 207 measurments
4: Got 213 measurments
5: Got 212 measurments
6: Got 212 measurments
7: Got 213 measurments
8: Got 207 measurments
9: Got 214 measurments
10: Got 218 measurments
11: Got 214 measurments
12: Got 211 measurments
13: Got 209 measurments
14: Got 214 measurments
15: Got 215 measurments
16: Got 210 measurments
17: Got 211 measurments
18: Got 214 measurments
19: Got 214 measurments
20: Got 212 measurments
21: Got 214 measurments
22: Got 206 measurments
23: Got 215 measurments
24: Got 216 measurments
25: Got 211 measurments
26: Got 213 measurments
27: Got 209 measurments
28: Got 211 measurments
29: Got 208 measurments
30: Got 206 measurments
31: Got 215 measurments
32: Got 207 measurments
33: Got 205 measurments
34: Got 215 measurments

在测试过程发现，思兰的激光雷达供电不足导致读取数据失败。所以树莓派的供电一定要足。

下图是测试场景。