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5IR LFR

Hardware
  • 1 Devlogs
  • 1 Total hours

A small robot that follows a black line with the help of 5 IR Sensors.

This needs changes before we can consider it shipped. Review the Shipwright feedback, make updates, then ship again.

This needs changes before we can consider it shipped. Review the Shipwright feedback, make updates, then ship again.

This needs changes before we can consider it shipped. Review the Shipwright feedback, make updates, then ship again.

This needs changes before we can consider it shipped. Review the Shipwright feedback, make updates, then ship again.

This needs changes before we can consider it shipped. Review the Shipwright feedback, make updates, then ship again.

This needs changes before we can consider it shipped. Review the Shipwright feedback, make updates, then ship again.

This needs changes before we can consider it shipped. Review the Shipwright feedback, make updates, then ship again.

This needs changes before we can consider it shipped. Review the Shipwright feedback, make updates, then ship again.

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1h 9m 21s logged

Today I started and completed my 5IR Line Follower Robot. I worked on the complete build process, including planning the sensor placement, making the circuit connections, and developing the code for the robot.

The robot uses 5 digital IR sensors connected with an ESP32 to detect the line. I created the sensor mapping and programmed the movement logic to control the motors through an L298N motor driver.

After testing and tuning the code, the robot was able to follow the track properly and handle different paths like curves, loops, and 90-degree turns. I also completed the power setup using two 2200mAh 3.7V Li-ion batteries with a buck converter for stable power.

The complete robot was built, coded, and tested successfully in around 1 hour.

Hardware used:

ESP32
5 Digital IR Sensors
L298N Motor Driver
300RPM Geared Motors
2x 2200mAh 3.7V Li-ion Batteries
Buck Converter
Robot Chassis

This was a quick prototype build to test my line following system and understand the performance of the sensor mapping and control logic.

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