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test.py
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test.py
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import numpy as np
import random
import utils
import cv2
import math
from GridMap import *
from ParticleFilter import *
from SingleBotLaser2D import *
import copy
def Draw(img_map, scale, bot_pos, sensor_data, bot_param):
img = img_map.copy()
img = cv2.resize(img, (round(scale*img.shape[1]), round(scale*img.shape[0])), interpolation=cv2.INTER_LINEAR)
img = utils.Map2Image(img)
plist = utils.EndPoint(bot_pos, bot_param, sensor_data)
for pts in plist:
cv2.line(
img,
(int(scale*bot_pos[0]), int(scale*bot_pos[1])),
(int(scale*pts[0]), int(scale*pts[1])),
(255,0,0), 1)
cv2.circle(img,(int(scale*bot_pos[0]), int(scale*bot_pos[1])), int(3*scale), (0,0,255), -1)
return img
def DrawParticle(img, plist, scale=1.0):
for p in plist:
cv2.circle(img,(int(scale*p.pos[0]), int(scale*p.pos[1])), int(2), (0,200,0), -1)
return img
def SensorMapping(m, bot_pos, bot_param, sensor_data):
inter = (bot_param[2] - bot_param[1]) / (bot_param[0]-1)
for i in range(bot_param[0]):
if sensor_data[i] > bot_param[3]-1 or sensor_data[i] < 1:
continue
theta = bot_pos[2] + bot_param[1] + i*inter
m.GridMapLine(
int(bot_pos[0]),
int(bot_pos[0]+sensor_data[i]*np.cos(np.deg2rad(theta))),
int(bot_pos[1]),
int(bot_pos[1]+sensor_data[i]*np.sin(np.deg2rad(theta)))
)
def AdaptiveGetMap(gmap):
mimg = gmap.GetMapProb(
gmap.boundary[0]-20, gmap.boundary[1]+20,
gmap.boundary[2]-20, gmap.boundary[3]+20 )
mimg = (255*mimg).astype(np.uint8)
mimg = cv2.cvtColor(mimg, cv2.COLOR_GRAY2RGB)
return mimg
if __name__ == '__main__':
# Initialize OpenCV Windows
cv2.namedWindow('view', cv2.WINDOW_AUTOSIZE)
cv2.namedWindow('map', cv2.WINDOW_AUTOSIZE)
# Initialize 2D Environment
# SensorSize, StartAngle, EndAngle, MaxDist, Velocity, Angular
bot_param = [240,-30.0, 210.0, 150.0, 6.0, 6.0]
bot_pos = np.array([150.0, 100.0, 0.0])
env = SingleBotLaser2Dgrid(bot_pos, bot_param, 'map_large.png')
# Initialize GridMap
# lo_occ, lo_free, lo_max, lo_min
map_param = [0.4, -0.4, 5.0, -5.0]
m = GridMap(map_param, gsize=1.0)
sensor_data = env.Sensor()
SensorMapping(m, env.bot_pos, env.bot_param, sensor_data)
img = Draw(env.img_map, 1, env.bot_pos, sensor_data, env.bot_param)
mimg = AdaptiveGetMap(m)
cv2.imshow('view',img)
cv2.imshow('map',mimg)
# Initialize Particle
pf = ParticleFilter(bot_pos.copy(), bot_param, copy.deepcopy(m), 10)
# Scan Matching Test
matching_m = GridMap(map_param, gsize=1.0)
SensorMapping(matching_m, env.bot_pos, env.bot_param, sensor_data)
matching_pos = np.array([150.0, 100.0, 0.0])
# Main Loop
while(1):
# Input Control
action = -1
k = cv2.waitKey(1)
if k==ord('w'):
action = 1
if k==ord('s'):
action = 2
if k==ord('a'):
action = 3
if k==ord('d'):
action = 4
if k==ord('i'):
action = 5
if k==ord('j'):
action = 6
if k==ord('l'):
action = 7
if k==ord('k'):
action = 8
if action > 0:
env.BotAction(action)
sensor_data = env.Sensor()
SensorMapping(m, env.bot_pos, env.bot_param, sensor_data)
img = Draw(env.img_map, 1, env.bot_pos, sensor_data, env.bot_param)
mimg = AdaptiveGetMap(m)
pf.Feed(action, sensor_data)
mid = np.argmax(pf.weights)
imgp0 = AdaptiveGetMap(pf.particle_list[mid].gmap)
img = DrawParticle(img, pf.particle_list)
cv2.imshow('view',img)
cv2.imshow('map',mimg)
cv2.imshow('particle_map',imgp0)
pf.Resampling(sensor_data)
cv2.destroyAllWindows()