Raspberry Pi Camera Line follower - RoboCup Junior Flanders 2014 - Robotanicus
https://happy-buy.ru/1gYwoIIj.php - купить на Али (Камера ночного видения Raspberry Pi 3B +, 5 МП, с сенсором Ov5647, широкоугольным модулем камеры Raspberry Pi 3 Model B/2) Внимание! Если ссылка ведет не на тот продукт, что Вы искали, воспользуйтесь поиском по сайту! EDIT: There's now a blog post on raspberrypi.org: RoboCup Junior competition Flanders 2014 - category 'Advanced Resue'. Looking for a new challenge, I decided to enter the RCJ competition for a second time, but this time using a camera and video analysis. So, I bought a Raspberry Pi and some stuff and learned programming in C++, using the openCV libraries, interfacing with the Pi Camera, and so on. The Raspberry Pi runs simultaneously a line following and a colour blob tracking algorithm. The RPi then sends the calculated data to the microcontroller, embedded in the Dwengo board, using the hardware serial port. I overclocked the Pi to 1GHz to get a frame rate of 12 to 14 fps. To interface the Pi Camera with openCV, I used Pierre Raufast's code, converted by Emil Valkov into a library. The Dwengo board receives the data with a serial interrupt. To calculate the error, the microcontroller applies additional calculations on the position data. It then processes the input of the IR long range sensor and controls the motors. Arne Baeyens - 2014 #Aliexpress #Алиэкспресс #Обзор #Товар #Распаковка
https://happy-buy.ru/1gYwoIIj.php - купить на Али (Камера ночного видения Raspberry Pi 3B +, 5 МП, с сенсором Ov5647, широкоугольным модулем камеры Raspberry Pi 3 Model B/2) Внимание! Если ссылка ведет не на тот продукт, что Вы искали, воспользуйтесь поиском по сайту! EDIT: There's now a blog post on raspberrypi.org: RoboCup Junior competition Flanders 2014 - category 'Advanced Resue'. Looking for a new challenge, I decided to enter the RCJ competition for a second time, but this time using a camera and video analysis. So, I bought a Raspberry Pi and some stuff and learned programming in C++, using the openCV libraries, interfacing with the Pi Camera, and so on. The Raspberry Pi runs simultaneously a line following and a colour blob tracking algorithm. The RPi then sends the calculated data to the microcontroller, embedded in the Dwengo board, using the hardware serial port. I overclocked the Pi to 1GHz to get a frame rate of 12 to 14 fps. To interface the Pi Camera with openCV, I used Pierre Raufast's code, converted by Emil Valkov into a library. The Dwengo board receives the data with a serial interrupt. To calculate the error, the microcontroller applies additional calculations on the position data. It then processes the input of the IR long range sensor and controls the motors. Arne Baeyens - 2014 #Aliexpress #Алиэкспресс #Обзор #Товар #Распаковка