星瞳实验室APP,快速收到回复
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  • CH340的USB转TTL支持吗



    • 用星瞳的串口助手能显示出串口但是连接后没有数据发送过来,是程序错了吗

      # Position_Control And Tracking Line - By: Linlin's Space - 周三 7月 5 2017
      
      import sensor, image, time, math,pyb
      from pyb import Pin, Timer,UART
      
      uart = pyb.UART(3,115200,timeout_char = 1000)#串口初始化
      
      # Tracks a black line. Use [(128, 255)] for a tracking a white line.
      GRAYSCALE_THRESHOLD = [(0, 100)]
      
      #ROIS = [                      #[ROI, weight]越近,权重越大,在这里权值暂时不考虑
      #        (7, 22,   50, 8, 0),#下面1
      #        (7, 12,   50, 8, 0),#中间2
      #        (7, 1,    50, 8, 0),#上面3
      #        (0, 0,    8, 31, 0),#左边4
      #        (56,0 ,   8, 31, 0) #右边5
      #       ]
      
      ROIS = [                            #[ROI, weight]越近,权重越大,在这里权值暂时不考虑
                     (0, 55,   64, 8, 0), #下面1
                     (0, 28,   64, 8, 0), #中间2
                     (0, 0,    64, 8, 0), #上面3
                     (0, 0,    8, 64, 0), #左边4
                     (56,0 ,   8, 64, 0)  #右边5
             ]
      weight_sum = 0
      for r in ROIS: weight_sum += r[4] # r[4] is the roi weight.
      
      
      #----------------------------------------寻找直线变量----------------------------------------#
      enable_lens_corr = False # turn on for straighter lines...
      min_degree = 0
      max_degree = 179
      a1=0;
      b1=0;
      c1=0;
      a2=0;
      b2=0;
      c2=0;
      last_x=0;
      last_y=0;
      #---------------------------------------摄像头初始化-----------------------------------------#
      
      sensor.reset()
      sensor.set_pixformat(sensor.GRAYSCALE)
      sensor.set_framesize(sensor.B64X64)                  # 颜色追踪:160*120  光流检测:40*30
      sensor.skip_frames(time=2000)
      sensor.set_auto_gain(False)                         # 颜色追踪关闭自动增益
      sensor.set_auto_whitebal(False)                     # 颜色追踪关闭白平衡
      Sum_x=0;
      Sum_y=0;
      flag=0;
      i=0;  #记录第几行数据
      j=0;  #记录直线数量
      led=pyb.LED(3)#必要的时候进行红外补光
      
      
      #检测圆形中心点的坐标
      center_x=0;
      center_y=0;
      center_update=1;#中心圆位置更新的标志
      center_x_old=0;
      center_y_old=0;
      center_pos_old=0;
      
      center_x_down=0;
      center_y_down=0;
      
      center_x_up=0;
      center_y_up=0;
      
      center_x_mid=0;
      center_y_mid=0;
      
      center_y_left=0;
      center_x_left=0;
      
      center_y_right=0;
      center_x_right=0;
      
      center_flag1=0;#上下
      center_flag2=0;#左右
      center_flag3=0;#通过roll来调整黑线的位置  通过yaw来调整机头方向  矩形1和2=0;
      center_flag4=0;
      center_flag5=0;
      
      turn_flag=0;#转弯的标志
      
      yaw_angle=0;
      out_str1='';
      clock = time.clock()
      #帧率
      #old_img= sensor.snapshot()        # 160x120 -> 40x30,前一张照片
      #定义一个定时发送数据的函数
      def tick(timer):#we will receive the timer object when being called
              global flag
              flag=1
      tim = Timer(4,freq=20)            # create a timer object using timer 4 - trigger at 1Hz
      tim.callback(tick)                # set the callback to our tick function
      #--------------------------------------while循环开始-----------------------------------------#
      
      while(True):
          #led.on()
          if(flag==1):
              img=sensor.snapshot()
              img_old=img.copy()
              #--------------------------------------光流定点-----------------------------------------#
              img.lens_corr(1.5) # for 2.8mm lens...摄像头畸变纠正
              #--------------------------------------检测直线交点的位置---------------------------------------#
              lines = img_old.find_lines(threshold=1000, theta_margin = 50, rho_margin = 50)
              for i in range(0,len(lines)-1):
                  for j in range(i+1,len(lines)):
                      l0x1 = lines[i].x1()
                      l0x2 = lines[i].x2()
                      l0y2 = lines[i].y2()
                      l0y1 = lines[i].y1()
                      if(l0x1 == l0x2):
                          l0x1 = l0x1 + 0.1
                      a0 = (l0y2 - l0y1)/(l0x2 - l0x1)
                      b0 = l0y1 - a0*l0x1
                      l1x1 = lines[j].x1()
                      l1y1 = lines[j].y1()
                      l1x2 = lines[j].x2()
                      l1y2 = lines[j].y2()
                      if(l1x1 == l1x2):
                          l1x1 = l1x1 + 0.1
                      a1 = (l1y2 - l1y1)/(l1x2 - l1x1)
                      b1 = l1y1 - a1*l1x1
                      if(a0==a1):
                          a0 = a0+ 0.1
                      intersectionx = (b1-b0)/(a0-a1)
      
                      intersectiony = a0*intersectionx + b0
      
                      #if(a0*a1 > -1.5 and a0*a1 < 0.7 ):
                      #img.draw_circle(int(intersectionx), int(intersectiony),10)
                      if((intersectionx-last_x)>2 or (intersectionx-last_x)<-2):
                          last_x=intersectionx;
                      if((intersectiony-last_y)>2 or (intersectiony-last_y)<-2):
                          last_y=intersectiony;
              #img.binary(GRAYSCALE_THRESHOLD,invert=1);
              #--------------------------------------寻找黑线和圆心的位置--------------------------------------#
              centroid_sum=0#暂时用不到这个变量
              #检测圆形位置
              for r in ROIS:
                  i=i+1;
                  blobs=img_old.find_blobs(GRAYSCALE_THRESHOLD, roi=r[0:4], merge=True,pixels_area=10) # r[0:4] is roi tuple.
                  if blobs:#如果找到了颜色块
                      # Find the blob with the most pixels.
                      largest_blob = max(blobs, key=lambda b: b.pixels())
                      if(i==1):#下面矩形
                          if(largest_blob[2]<=15 and largest_blob[2]>=2):#排除瑕疵点
                              if(largest_blob[3]>=2):
                                  center_x_down=largest_blob.cx();
                                  center_y_down=largest_blob.cy();
                                  center_flag1=1;#下面的矩形找到的标志
                                  img.draw_rectangle(largest_blob.rect())
                                  img.draw_cross(largest_blob.cx(),largest_blob.cy(),2)
      
                      elif(i==2):#中间矩形
                          if(largest_blob[2]<=15 and largest_blob[2]>=2):
                              if(largest_blob[3]>=2):
                                  center_x_mid=largest_blob.cx();
                                  center_y_mid=largest_blob.cy();
                                  center_flag2=1;
                                  img.draw_rectangle(largest_blob.rect())
                                  img.draw_cross(largest_blob.cx(),largest_blob.cy(),2)
                      elif(i==3):#上面的矩形
                          center_flag3=2;#有找到,但是不符合要求
                          if(largest_blob[2]<=10 and largest_blob[2]>=2):
                              if(largest_blob[3]>=2):
                                  center_x_up=largest_blob.cx();
                                  center_y_up=largest_blob.cy();
                                  center_flag3=1;
                                  img.draw_rectangle(largest_blob.rect())
                                  img.draw_cross(largest_blob.cx(),largest_blob.cy(),2)
                      elif(i==4):#左边的矩形找到了
                          if(largest_blob[3]<=15 and largest_blob[3]>=2):
                              if(largest_blob[2]>=2):
                                  center_y_left=largest_blob.cy();
                                  center_x_left=largest_blob.cx();
                                  center_flag4=1;
                                  img.draw_rectangle(largest_blob.rect())
                                  img.draw_cross(largest_blob.cx(),largest_blob.cy(),2)
                      elif(i==5):
                          if(largest_blob[3]<=15 and largest_blob[3]>=2):
                              if(largest_blob[2]>=2):
                                  center_y_right=largest_blob.cy();
                                  center_x_right=largest_blob.cx();
                                  center_flag5=1;
                                  img.draw_rectangle(largest_blob.rect())
                                  img.draw_cross(largest_blob.cx(),largest_blob.cy(),2)
              for l in lines:#画出所有的直线
                  img.draw_line(l.line())
              img.draw_cross(int(last_x), int(last_y),3,color=0)
              img.draw_circle(int(last_x), int(last_y),3,color=0)
              #print(last_x,last_y)
              #1开始计算中心圆x坐标
              if(center_flag1==1 and center_flag3!=1):
                  center_x=center_x_down;
              elif(center_flag1==0 and center_flag3==1):
                  center_x=center_x_up;
              elif(center_flag1==1 and center_flag3==1):
                  center_x=int((center_x_up+center_x_down)/2)#这样计算即使机头偏离了十字中心,中心点位置也是准确地
              else:
                  center_x=center_x_old;#如果没找到就返回上一次的值
      
              #2开始计算中心圆y坐标
              if(center_flag4==1   and center_flag5==0):
                  center_y=center_y_left;
              elif(center_flag4==0 and center_flag5==1):
                  center_y=center_y_right;
              elif(center_flag4==1 and center_flag5==1):
                  center_y=int((center_y_left+center_y_right)/2)
              else:
                  center_y=center_y_old;#如果没找到就返回上一次的值
              center_x_old=center_x;
              center_y_old=center_y;
              img.draw_circle(center_x,center_y,3);
              img.draw_cross(center_x,center_y,3);
      
              #3开始检测直角
              #if(center_flag3==0 and center_flag1==1 and center_flag4==1):
              if(center_flag3==0 and center_flag1==1 and center_flag4==1):
                  turn_flag=1;#左转
                  print("left")
              if(center_flag3==0 and center_flag1==1 and center_flag5==1):
                  turn_flag=1;#右转
              if(center_flag1==0):
                  center_x_down=32;
              if(center_flag2==0):
                  center_x_mid=32;
              if(center_flag3!=1):
                  center_x_up=32;
              center_pos=int(center_x_down+center_x_mid+center_x_up)/3
      
              if(center_flag1==0 and center_flag2==0 and center_flag3==0):
                  center_pos=center_pos_old
              center_pos_old=center_pos
              #距离中心点位置不能超过+-5cm
              #标记出来圆形,便于查看中心坐标,用于进行定点起飞和降落
      
              #开始进行YAW纠正,三条线都在视野内开始进行偏航纠正
              if(center_flag1==1 and center_flag2==1 and center_flag3==1):
                  yaw_angle =math.atan(float(center_x_)/float())
                  yaw_angle =math.degrees(yaw_angle)
      
              center_flag1=0;#标志清零
              center_flag2=0;#标志清零
              center_flag3=0;
              center_flag4=0;
              center_flag5=0;
              i=0;
      
              #50ms发送一次数据到飞控
              if(yaw_angle<0):
                  out_str1='-'
                  out_str1+= '%.2d'% int(-yaw_angle)    #寻找黑线中心位置计算出偏转角度
              else:
                  out_str1='+'
                  out_str1+= '%.2d'% int(yaw_angle)     #寻找黑线中心位置计算出偏转角度
              if(Sum_x<0):
                  out_str1+='-'
                  out_str1+='%.2d'%  int(-Sum_x);       #光流数据
              else:
                  out_str1+='+'
                  out_str1+='%.2d'%  int(Sum_x)         #寻找黑线中心位置计算出偏转角度
              if(Sum_y<0):
                  out_str1+='-'
                  out_str1+= '%.2d'% int(-Sum_y);       #光流数据
              else:
                  out_str1+='+'
                  out_str1+= '%.2d'% int(Sum_y);        #光流数据
      
              out_str1+='%.2d'%      int(center_pos);
              out_str1+='%.2d'%      int(center_x);    #圆心的位置
              out_str1+='%.2d'%      int(center_y);
              out_str1+='%.2d'%      int(turn_flag);   #直角标志位
              out_str1+='%.2d'%      int(last_x);      #直角交点位置
              out_str1+='%.2d'%      int(last_y);
              uart.write('s'+out_str1+'#')
              #print(out_str1)
              #像素位移之和清零
              turn_flag=0;
              yaw_angle=0;
              Sum_x=0
              Sum_y=0
              #print("%0.1f Xcm  %0.1f Ycm  %0.2fQ\t" %(Sum_x,Sum_y,response))
              #数组清零
              out_str1=''#清除之前的数据
              flag=0;
              #-----------------------------------串口打印数据-----------------------------------------#
      
      
      
      
      


    • 当然是支持的。
      请运行测试程序:http://book.openmv.cc/example/02-Board-Control/uart-control.html

      如果还不行,要么是线没接好,要么是串口助手没点击连接。

      建议使用OpenMV配套的串口调试扩展板:
      https://singtown.com/product/49906/openmv串口调试扩展板/