add no.20

This commit is contained in:
litian.zhuang 2022-06-09 19:52:27 +08:00
parent acb097794d
commit e29d15e6eb
6 changed files with 501 additions and 11 deletions

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@ -9,7 +9,7 @@ export PATH
# SPARK技术讨论与反馈QQ群6646169 8346256 # SPARK技术讨论与反馈QQ群6646169 8346256
#================================================= #=================================================
GAME_ENABLE="yes" GAME_ENABLE="no"
sh_ver="2.0" sh_ver="2.0"
filepath=$(cd "$(dirname "$0")"; pwd) filepath=$(cd "$(dirname "$0")"; pwd)
Green_font_prefix="\033[32m" && Red_font_prefix="\033[31m" && Green_background_prefix="\033[42;37m" && Red_background_prefix="\033[41;37m" && Yellow_background_prefix="\033[43;37m" && Font_color_suffix="\033[0m" && Yellow_font_prefix="\e[1;33m" && Blue_font_prefix="\e[0;34m" Green_font_prefix="\033[32m" && Red_font_prefix="\033[31m" && Green_background_prefix="\033[42;37m" && Red_background_prefix="\033[41;37m" && Yellow_background_prefix="\033[43;37m" && Font_color_suffix="\033[0m" && Yellow_font_prefix="\e[1;33m" && Blue_font_prefix="\e[0;34m"
@ -98,6 +98,21 @@ check_lidar(){
echo -e "${Error} 没有找到雷达,请确认雷达已正确连接!!" echo -e "${Error} 没有找到雷达,请确认雷达已正确连接!!"
fi fi
} }
check_camera_no_print(){
#检查使用哪种设备
if [ -n "$(lsusb -d 2bc5:0403)" ]; then
CAMERATYPE="astrapro"
fi
if [ -n "$(lsusb -d 2bc5:0401)" ]; then
CAMERATYPE="astra"
fi
if [ -n "$(lsusb -d 8086:0b07)" ]; then
CAMERATYPE="d435"
fi
}
#检查摄像头设备 #检查摄像头设备
check_camera(){ check_camera(){
@ -752,14 +767,49 @@ spark_dock(){
} }
#让SPARK夺宝奇兵比赛用示例程序 #hsv范围值查找
spark_hsv_detection(){
echo -e "${Info}"
echo -e "${Info}hsv值自动查找"
ROSVER=`/usr/bin/rosversion -d`
PROJECTPATH=$(cd `dirname $0`; pwd)
source ${PROJECTPATH}/devel/setup.bash
echo -e "${Info}"
echo -e "${Info}请确定:"
echo -e "${Info} A.摄像头已反向向下安装好。机械臂正常上电。"
echo -e "${Info} B.${Red_font_prefix}红色${Font_color_suffix}标定物已贴好在吸盘固定头正上方。"
echo -e "${Info} C.机械臂正常上电。"
echo -e "${Info}退出请输入Ctrl + c "
echo -e "${Info}"
echo -e "${Info}请选择比赛方式:
${Green_font_prefix}1.${Font_color_suffix} 获取吸盘上方hsv值
${Green_font_prefix}2.${Font_color_suffix} 获取颜色块hsv值,需要将颜色块放在图像的矩形框中
${Green_font_prefix}3.${Font_color_suffix} 退出请输入Ctrl + c"
echo && stty erase ^? && read -p "请输入数字 [1-2]" armnum
case "$armnum" in
1)
roslaunch spark_carry_object hsv_detection.launch camera_type_tel:=${CAMERATYPE} color:=${calibration}
;;
2)
roslaunch spark_carry_object hsv_detection.launch camera_type_tel:=${CAMERATYPE} color:=${color_block}
;;
*)
echo -e "${Error} 错误,请填入正确的数字"
;;
esac
}
#方块抓取示例程序
spark_carry_game(){ spark_carry_game(){
echo -e "${Info}" echo -e "${Info}"
echo -e "${Info}夺宝奇兵比赛用示例程序" echo -e "${Info}夺宝奇兵比赛用示例程序"
ROSVER=`/usr/bin/rosversion -d` ROSVER=`/usr/bin/rosversion -d`
PROJECTPATH=$(cd `dirname $0`; pwd) PROJECTPATH=$(cd `dirname $0`; pwd)
source ${PROJECTPATH}/devel/setup.bash source ${PROJECTPATH}/devel/setup.bash
echo -e "${Info}请选择比赛方式: echo -e "${Info}请选择方式:
${Green_font_prefix}1.${Font_color_suffix} 手动模式 ${Green_font_prefix}1.${Font_color_suffix} 手动模式
${Green_font_prefix}2.${Font_color_suffix} 自动模式 ${Green_font_prefix}2.${Font_color_suffix} 自动模式
${Green_font_prefix}3.${Font_color_suffix} 退出请输入Ctrl + c" ${Green_font_prefix}3.${Font_color_suffix} 退出请输入Ctrl + c"
@ -992,6 +1042,23 @@ coming_soon(){
} }
check_camera_game(){
if [[ "${GAME_ENABLE}" == "yes" ]]; then
check_camera_no_print
if [[ "${CAMERATYPE}" == "d435" ]]; then
aa='a'
else
echo -e "
${Green_font_prefix} 13.${Font_color_suffix} hsv值自动查找"
fi
echo -e "
${Green_font_prefix} 20.${Font_color_suffix} 竞赛示例程序
————————————"
fi
}
#printf #printf
menu_status(){ menu_status(){
echo -e "${Tip} 当前系统版本 ${OSDescription} !" echo -e "${Tip} 当前系统版本 ${OSDescription} !"
@ -1043,10 +1110,9 @@ echo -e "
${Green_font_prefix} 11.${Font_color_suffix} 语音控制SPARK移动 ${Green_font_prefix} 11.${Font_color_suffix} 语音控制SPARK移动
${Green_font_prefix} 12.${Font_color_suffix} 给摄像头做标定 ${Green_font_prefix} 12.${Font_color_suffix} 给摄像头做标定
${Green_font_prefix} 20.${Font_color_suffix} 比赛程序 ————————————"
check_camera_game
———————————— echo -e "
${Green_font_prefix}100.${Font_color_suffix} 问题反馈 ${Green_font_prefix}100.${Font_color_suffix} 问题反馈
${Green_font_prefix}104.${Font_color_suffix} 文件传输 ${Green_font_prefix}104.${Font_color_suffix} 文件传输
" "
@ -1093,6 +1159,9 @@ case "$num" in
12) 12)
calibrate_camera calibrate_camera
;; ;;
13)
spark_hsv_detection
;;
20) 20)
spark_carry_game spark_carry_game
;; ;;

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@ -51,7 +51,7 @@
</node> </node>
</group> </group>
<group if="$(eval arg('camera_type_tel')=='astrapro')"> <group if="$(eval arg('camera_type_tel')=='astrapro')">
<node pkg="move2grasp" type="grasp_pro.py" name="grasp" /> <node pkg="move2grasp" type="grasp_pro_new.py" name="grasp" />
</group> </group>
</launch> </launch>

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@ -15,6 +15,7 @@
<arg name="camera_type_tel" value="$(arg camera_type_tel)"/> <arg name="camera_type_tel" value="$(arg camera_type_tel)"/>
<arg name="lidar_type_tel" value="$(arg lidar_type_tel)"/> <arg name="lidar_type_tel" value="$(arg lidar_type_tel)"/>
<arg name="start_camera" value="true"/>
</include> </include>
@ -53,7 +54,7 @@
</node> </node>
</group> </group>
<group if="$(eval arg('camera_type_tel')=='astrapro')"> <group if="$(eval arg('camera_type_tel')=='astrapro')">
<node pkg="move2grasp" type="grasp_pro.py" name="grasp" /> <node pkg="move2grasp" type="grasp_pro_new.py" name="grasp" output="screen"/>
</group> </group>
</launch> </launch>

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@ -0,0 +1,263 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
import os
import time
import random
import ctypes
import roslib
import rospy
import smach
import smach_ros
import threading
import string
import math
import cv2
import numpy as np
from geometry_msgs.msg import Twist
from std_msgs.msg import String
from geometry_msgs.msg import Pose, Point, Quaternion
from sensor_msgs.msg import Image
from cv_bridge import CvBridge, CvBridgeError
from spark_carry_object.msg import *
class GraspObject():
'''
监听主控用于物品抓取功能
'''
def __init__(self):
'''
初始化
'''
global xc, yc, xc_prev, yc_prev, found_count
xc = 0
yc = 0
xc_prev = xc
yc_prev = yc
found_count = 0
self.is_found_object = False
# self.sub = rospy.Subscriber("/camera/rgb/image_raw", Image, self.image_cb, queue_size=1)
# 订阅机械臂抓取指令
self.sub2 = rospy.Subscriber(
'/grasp', String, self.grasp_cp, queue_size=1)
# 发布机械臂位姿
self.pub1 = rospy.Publisher(
'position_write_topic', position, queue_size=10)
# 发布机械臂吸盘
self.pub2 = rospy.Publisher('pump_topic', status, queue_size=1)
# 发布机械臂状态
self.grasp_status_pub = rospy.Publisher(
'grasp_status', String, queue_size=1)
# 发布TWist消息控制机器人底盘
self.cmd_vel_pub = rospy.Publisher('/cmd_vel', Twist, queue_size=1)
pos = position()
pos.x = 120
pos.y = 0
pos.z = 35
self.pub1.publish(pos)
def grasp_cp(self, msg):
if msg.data == '1':
# 订阅摄像头话题,对图像信息进行处理
self.sub = rospy.Subscriber("/camera/rgb/image_raw", Image, self.image_cb, queue_size=1)
self.is_found_object = False
rate = rospy.Rate(10)
times=0
steps=0
while not self.is_found_object:
rate.sleep()
times+=1
# 转一圈没有发现可抓取物体,退出抓取
if steps>=5:
self.sub.unregister()
print("stop grasp\n")
status=String()
status.data='-1'
self.grasp_status_pub.publish(status)
return
# 旋转一定角度扫描是否有可供抓取的物体
if times>=30:
times=0
steps+=1
self.turn_body()
print("not found\n")
print("unregisting sub\n")
self.sub.unregister()
print("unregisted sub\n")
# 抓取检测到的物体
self.grasp()
status=String()
status.data='1'
self.grasp_status_pub.publish(status)
if msg.data=='0':
# 放下物体
self.is_found_object = False
self.release_object()
status=String()
status.data='0'
self.grasp_status_pub.publish(status)
# 执行抓取
def grasp(self):
print("start to grasp\n")
global xc, yc, found_count
# stop function
filename = os.environ['HOME'] + "/thefile.txt"
file_pix = open(filename, 'r')
s = file_pix.read()
file_pix.close()
print(s)
arr=s.split()
a1=arr[0]
a2=arr[1]
a3=arr[2]
a4=arr[3]
a = [0]*2
b = [0]*2
a[0]=float(a1)
a[1]=float(a2)
b[0]=float(a3)
b[1]=float(a4)
print('k and b value:',a[0],a[1],b[0],b[1])
r1 = rospy.Rate(0.095)
r2 = rospy.Rate(10)
pos = position()
# 物体所在坐标+标定误差
pos.x = a[0] * yc + a[1]
pos.y = b[0] * xc + b[1]
pos.z = 20
# pos.z = 20
print("z = 20\n")
self.pub1.publish(pos)
r2.sleep()
# go down -100
pos.z = -50
self.pub1.publish(pos)
print("z = -83\n")
r2.sleep()
# 开始吸取物体
self.pub2.publish(1)
r2.sleep()
# 提起物体
pos.x = 250 #160
pos.y = 0
pos.z = 150 #55
self.pub1.publish(pos)
r1.sleep()
# 使用CV检测物体
def image_cb(self, data):
global xc, yc, xc_prev, yc_prev, found_count
# change to opencv
try:
cv_image1 = CvBridge().imgmsg_to_cv2(data, "bgr8")
except CvBridgeError as e:
print('error')
# change rgb to hsv
cv_image2 = cv2.cvtColor(cv_image1, cv2.COLOR_BGR2HSV)
# 蓝色物体颜色检测范围
LowerBlue = np.array([95, 70, 60])
UpperBlue = np.array([140, 255, 255])
mask = cv2.inRange(cv_image2, LowerBlue, UpperBlue)
cv_image3 = cv2.bitwise_and(cv_image2, cv_image2, mask=mask)
# gray process
cv_image4 = cv_image3[:, :, 0]
# smooth and clean noise
blurred = cv2.blur(cv_image4, (9, 9))
(_, thresh) = cv2.threshold(blurred, 90, 255, cv2.THRESH_BINARY)
kernel = cv2.getStructuringElement(cv2.MORPH_RECT, (25, 25))
cv_image5 = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel)
cv_image5 = cv2.erode(cv_image5, None, iterations=4)
cv_image5 = cv2.dilate(cv_image5, None, iterations=4)
# detect contour
# cv2.imshow("win1", cv_image3)
# cv2.imshow("win2", cv_image5)
cv2.waitKey(1)
contours, hier = cv2.findContours(cv_image5, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE)
# if find contours, pick the biggest box
if len(contours) > 0:
size = []
size_max = 0
for i, c in enumerate(contours):
rect = cv2.minAreaRect(c)
box = cv2.boxPoints(rect)
box = np.int0(box)
x_mid = (box[0][0] + box[2][0] + box[1][0] + box[3][0]) / 4
y_mid = (box[0][1] + box[2][1] + box[1][1] + box[3][1]) / 4
w = math.sqrt((box[0][0] - box[1][0]) ** 2 + (box[0][1] - box[1][1]) ** 2)
h = math.sqrt((box[0][0] - box[3][0]) ** 2 + (box[0][1] - box[3][1]) ** 2)
size.append(w * h)
if size[i] > size_max:
size_max = size[i]
index = i
xc = x_mid
yc = y_mid
# if box is not moving for 20 times
# print found_count
if found_count >= 30:
self.is_found_object = True
cmd_vel = Twist()
self.cmd_vel_pub.publish(cmd_vel)
else:
# if box is not moving
if abs(xc - xc_prev) <= 2 and abs(yc - yc_prev) <= 2:
found_count = found_count + 1
else:
found_count = 0
else:
found_count = 0
xc_prev = xc
yc_prev = yc
# 释放物体
def release_object(self):
r1 = rospy.Rate(0.15) # 5s
r2 = rospy.Rate(1) # 1s
pos = position()
# go forward
pos.x = 200
pos.y = 0
pos.z = -40 #-80
self.pub1.publish(pos)
r1.sleep()
# stop pump
self.pub2.publish(0)
r2.sleep()
#r1.sleep()
pos.x = 120
pos.y = 0
pos.z = 35
self.pub1.publish(pos)
r1.sleep()
return 'succeeded'
# 转动机器人到一定角度
def turn_body(self):
cmd_vel = Twist()
cmd_vel.angular.z = 0.25
rate = rospy.Rate(10)
for i in range(40):
self.cmd_vel_pub.publish(cmd_vel)
rate.sleep()
if __name__ == '__main__':
try:
rospy.init_node('GraspObject', anonymous=False)
rospy.loginfo("Init GraspObject main")
GraspObject()
rospy.spin()
except rospy.ROSInterruptException:
rospy.loginfo("End spark GraspObject main")

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@ -33,7 +33,7 @@ def keyboardLoop():
#速度变量 #速度变量
# 慢速 # 慢速
walk_vel_ = rospy.get_param('walk_vel', 0.3) walk_vel_ = rospy.get_param('walk_vel', 0.2)
# 快速 # 快速
run_vel_ = rospy.get_param('run_vel', 1.0) run_vel_ = rospy.get_param('run_vel', 1.0)
yaw_rate_ = rospy.get_param('yaw_rate', 1.0) yaw_rate_ = rospy.get_param('yaw_rate', 1.0)
@ -72,12 +72,16 @@ def keyboardLoop():
msg.data='1' msg.data='1'
grasp_pub.publish(msg) grasp_pub.publish(msg)
can_grasp=False can_grasp=False
speed = 0
turn = 0
elif ch == 'h': elif ch == 'h':
if can_release: if can_release:
msg=String() msg=String()
msg.data='0' msg.data='0'
grasp_pub.publish(msg) grasp_pub.publish(msg)
can_release=False can_release=False
speed = 0
turn = 0
elif ch == 'w': elif ch == 'w':
max_tv = walk_vel_ max_tv = walk_vel_
speed = 1 speed = 1
@ -124,7 +128,7 @@ def keyboardLoop():
pub.publish(cmd) pub.publish(cmd)
rate.sleep() rate.sleep()
#停止机器人 #停止机器人
stop_robot() #stop_robot()
def stop_robot(): def stop_robot():
cmd.linear.x = 0.0 cmd.linear.x = 0.0

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@ -0,0 +1,153 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import cv2
import numpy as np
import math
import os
import sys
import time
from PIL import Image, ImageDraw,ImageFont
import rospy
from spark_carry_object.msg import *
def mean_hsv(img,HSV_value):
HSV = cv2.cvtColor(img, cv2.COLOR_BGR2HSV)
HSV_value[0]+=np.mean(HSV[:, :, 0])
HSV_value[1]+=np.mean(HSV[:, :, 1])
HSV_value[2]+=np.mean(HSV[:, :, 2])
return HSV_value
def hsv_range(HSV_value):
# 设置HSV颜色值的范围
H_range = 12
S_range = 120
V_range = 120
lower_H = int(HSV_value[0] - H_range)
upper_H = int(HSV_value[0] + H_range)
lower_S = int(HSV_value[1] - S_range)
upper_S = int(HSV_value[1] + S_range)
lower_V = int(HSV_value[2] - V_range)
upper_V = int(HSV_value[2] + V_range)
if lower_H<0:
lower_H=0
if upper_H>180:
upper_H=180
if lower_S<50:
lower_S=50
if upper_S>255:
upper_S=255
if lower_V<50:
lower_V=50
if upper_V>255:
upper_V=255
lower_HSV = np.array([lower_H, lower_S, lower_V])
upper_HSV = np.array([upper_H, upper_S, upper_V])
return lower_HSV, upper_HSV
def test(lower_HSV, upper_HSV, image):
hsv = cv2.cvtColor(image, cv2.COLOR_BGR2HSV)
mask = cv2.inRange(hsv, lower_HSV, upper_HSV)
mask = cv2.erode(mask, None, iterations=2)
mask = cv2.dilate(mask, None, iterations=2)
mask = cv2.GaussianBlur(mask, (3, 3), 0)
cv2.putText(mask, 'Done! Press q to exit!', (30, 30), cv2.FONT_HERSHEY_SIMPLEX, 1.2,
(255, 255, 255), 2, cv2.LINE_AA)
cv2.imshow("HSV_img", mask)
def arm_init():
pub1 = rospy.Publisher('position_write_topic', position, queue_size=1)
r1 = rospy.Rate(1)
r1.sleep()
pos = position()
pos.x = 120
pos.y = 0
pos.z = 35
pub1.publish(pos)
r1.sleep()
def save_hsv(name, lower_HSV, upper_HSV):
content = str(lower_HSV[0]) + ',' +str(lower_HSV[1])+ ',' + str(lower_HSV[2]) \
+ ' ' + str(upper_HSV[0])+ ',' + str(upper_HSV[1])+ ',' + str(upper_HSV[2]) + '\n'
# 将HSV值写入文件文件在spark目录下
if name == 'color_block':
content = "block_HSV is :" + content
filename = os.environ['HOME'] + "/color_block_HSV.txt"
elif name == 'calibration':
content = "calibration_HSV is :" + content
filename = os.environ['HOME'] + "/calibration_HSV.txt"
with open(filename, "w") as f:
f.write(content)
print("HSV value has saved in" + filename)
print(content)
def main():
name = rospy.get_param("/spark_hsv_detection/color")
arm_init()
time.sleep(3)
HSV_value = [0,0,0]
count = 0
capture = cv2.VideoCapture(0)
# 颜色块中心点上下左右扩大60个像素
box_w = 60
# 吸盘上方颜色像素范围
cali_w = 20
cali_h = 30
# 收集300次取平均值
collect_times = 300
while True:
ret, img = capture.read()
if img is not None:
# 200次以内先做提醒将颜色块放在矩形框中
if count < 200:
cv2.putText(img, 'please put the color being', (30, 30), cv2.FONT_HERSHEY_SIMPLEX, 1.2,
(0, 255, 0), 2, cv2.LINE_AA)
cv2.putText(img, 'tested in rectangle box!', (30, 80), cv2.FONT_HERSHEY_SIMPLEX, 1.2,
(0, 255, 0), 2, cv2.LINE_AA)
# 如果在200-500次以内开始收集hsv值并求出平均值
elif count > 200 and count < 200+collect_times:
cv2.putText(img, 'HSV_value is collecting!', (30, 30), cv2.FONT_HERSHEY_SIMPLEX, 1.2,
(0, 255, 0), 2, cv2.LINE_AA)
if name == 'color_block':
frame = img[120:120 + box_w, 300:300 + box_w]
elif name == 'calibration':
frame = img[310:310 + cali_h, 355:355 + cali_w]
HSV_value = mean_hsv(frame, HSV_value)
# 500次以后开始检测查看是否有提取到矩形框中颜色的HSV值
elif count==200+collect_times:
for i in range(len(HSV_value)):
HSV_value[i] = HSV_value[i] / collect_times
lower_HSV, upper_HSV = hsv_range(HSV_value)
save_hsv(name, lower_HSV, upper_HSV)
elif count > 200+collect_times:
test(lower_HSV, upper_HSV, img)
count += 1
if name == 'color_block':
cv2.rectangle(img, (300, 120), (300+box_w, 120+box_w), (0, 255, 0), 3)
elif name == 'calibration':
cv2.rectangle(img, (355, 310), (355 + cali_w, 310 + cali_h), (0, 255, 0), 3)
cv2.imshow("RGB_img", img)
cv2.waitKey(1)
if cv2.waitKey(10) == ord('q'):
break
cv2.destroyAllWindows()
return lower_HSV, upper_HSV
if __name__ == '__main__':
rospy.init_node('hsv_detection', anonymous=True)
main()
rospy.spin()