안녕하세요
제공해준 예제 중에 '10_RC_CAR_Obstacle' 예제에 대한 질문입니다.
직진하다가 25cm이내에 초음파 센서 범위에 들어오면 '우회전', '좌회전'하여 해당 방향의 거리를 측정하고 여유있는 곳으로 이동해야하는데
직진은 하지않고 후진만 하네요.
if(Ultra_d < 250) { << 범위가 좁은거 같아 500, 1000 으로 늘려서 테스트를 해봐도 그대로 입니다.
Ultra_d = Ultrasonic();
Serial.println(Ultra_d);
motor_role(HIGH, HIGH); // 직진
Serial.println("직진"); << 혹시나 싶어 println 문은 넣어서 테스트 해봤는데
![](data:image/png;base64,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)
println에 직진은 나와있는데 직진은 하지 않았습니다.
참고로 그 이전 예제들은 모두 문제없이 실행되었습니다. 이 부분에 막혀서 질문을 드립니다.
초음파센서 선 연결 및 건전지 배터리량까지 체크했습니다.
void loop() {
Ultra_d = Ultrasonic();
Serial.println(Ultra_d);
motor_role(HIGH, HIGH);
if(Ultra_d < 250) {
if (Ultra_d < 150) {
Serial.println("150 이하.");
motor_role(LOW, LOW); // 후진
delay(1000);
analogWrite(RightMotor_E_pin, 0);
analogWrite(LeftMotor_E_pin, 0);
delay(200);
}
else {
analogWrite(RightMotor_E_pin, 0);
analogWrite(LeftMotor_E_pin, 0);
delay(200);
Serial.println("150 이상.");
val = Servo_con();
if (val == 0) {
Serial.println("우회전.");
analogWrite(RightMotor_E_pin, 0);
analogWrite(LeftMotor_E_pin, 0);
delay(500);
motor_role(LOW, LOW); // 후진
delay(500);
motor_role(LOW, HIGH); // 우회전
delay(800);
}
else if (val == 1) {
Serial.println("좌회전.");
analogWrite(RightMotor_E_pin, 0);
analogWrite(LeftMotor_E_pin, 0);
delay(500);
motor_role(LOW, LOW); // 후진
delay(500);
motor_role(HIGH, LOW); // 좌회전
delay(800);
}
}
}
}
(실제로는 전진 명령인데 바퀴가 반대로 꽂혀 있어서 후진하는 식)
모터선의 빨간 색과 검은 색을 반대로 꼽아보세요