主要是说缓冲区太小的问题，目前找不到解决办法，使用的是例程视频里面的循迹小车部分，就是主函数里面多加了一个串口发送的，发送出去输出的output的有符号的值，每当一遇到跳变很大的或者如遇到图片情况就会报错：
Traceback (most recent call last):
File "", line 39, in ：第39行是sending_data(int(output))
File "", line 9, in sending_data：第9行是byte_value = data1.to_bytes(1, 'big', True)
OverflowError: buffer too small
OpenMV v4.6.20; MicroPython v1.24.62; OPENMV4P with STM32H743
Type "help()" for more information.

main.py

THRESHOLD = (1, 28, -21, 5, -20, 35)
import sensor,image,time,gc
from pyb import LED
from pid import PID
from pyb import UART
uart = UART(3,115200,bits=8, parity=None, stop=1,  timeout_char=2000, read_buf_len=1024)
def sending_data(data1):
    global uart
    byte_value = data1.to_bytes(1, 'big', True)
    data = bytearray([0x23, byte_value[0], 0x40])
    uart.write(data);
rho_pid = PID(p=0.6, i=0, d=0.15)
theta_pid = PID(p=0.003, i=0, d=0.002)
LED(1).on()
LED(2).on()
LED(3).on()
sensor.reset()
sensor.set_vflip(True)
sensor.set_hmirror(True)
sensor.set_pixformat(sensor.RGB565)
sensor.set_framesize(sensor.QQQVGA)
sensor.skip_frames(time = 2000)
clock = time.clock()
while(True):
    clock.tick()
    img = sensor.snapshot().binary([THRESHOLD])
    line = img.get_regression([(100,100)], robust = True)
    if (line):
        rho_err = abs(line.rho())-img.width()/2
        if line.theta()>90:
            theta_err = line.theta()-180
        else:
            theta_err = line.theta()
        img.draw_line(line.line(), color = 127)
        if line.magnitude()>8:
            rho_output = rho_pid.get_pid(rho_err,1)
            theta_output = theta_pid.get_pid(theta_err,1)
            output = rho_output+theta_output
            sending_data(int(output))
            print(int(output))
        pass
    gc.collect()

pid.py

from pyb import millis
from math import pi, isnan
class PID:
	_kp = _ki = _kd = _integrator = _imax = 0
	_last_error = _last_derivative = _last_t = 0
	_RC = 1/(2 * pi * 20)
	def __init__(self, p=0, i=0, d=0, imax=0):
		self._kp = float(p)
		self._ki = float(i)
		self._kd = float(d)
		self._imax = abs(imax)
		self._last_derivative = float('nan')
	def get_pid(self, error, scaler):
		tnow = millis()
		dt = tnow - self._last_t
		output = 0
		if self._last_t == 0 or dt > 1000:
			dt = 0
			self.reset_I()
		self._last_t = tnow
		delta_time = float(dt) / float(1000)
		output += error * self._kp
		if abs(self._kd) > 0 and dt > 0:
			if isnan(self._last_derivative):
				derivative = 0
				self._last_derivative = 0
			else:
				derivative = (error - self._last_error) / delta_time
			derivative = self._last_derivative + \
									 ((delta_time / (self._RC + delta_time)) * \
										(derivative - self._last_derivative))
			self._last_error = error
			self._last_derivative = derivative
			output += self._kd * derivative
		output *= scaler
		if abs(self._ki) > 0 and dt > 0:
			self._integrator += (error * self._ki) * scaler * delta_time
			if self._integrator < -self._imax: self._integrator = -self._imax
			elif self._integrator > self._imax: self._integrator = self._imax
			output += self._integrator
		return output
	def reset_I(self):
		self._integrator = 0
		self._last_derivative = float('nan')
``![0_1747998392094_屏幕截图 2025-05-23 190501.png](https://fcdn.singtown.com/4bb1afed-7417-4a7d-84aa-16d37f5cb692.png) `
:crying_face: 



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