Petoi AI Vision

Function introduction

Petoi AI Vision Module is based on the Arm Cortex-M55, and Ethos-U55 embedded vision module. The Ethos-U55 has 64 to 512 GOP/s of arithmetic power to meet the growing demand for downloading machine learning.

Hardware setup

BiBoard V0

Bittle X: BiBoard V0 with AI vision module
Bittle X

BiBoard V1

Bittle X: BiBoard V1 with AI vision module
Bittle X
Bittle X+Arm: BiBoard V1 with AI vision module
Bittle X+Arm

Fix the end connected to the camera to the robot's head (included in Bittle's / Bittle X's mouth or attached to Bittle X+Arm's robotic arm).

If you use the version of Petoi Desktop App <= V1.2.5, you need to connect the Petoi AI vision module to the following Grove socket: Bittle X

Bittle X+Arm

Software setup

There are two methods to upload the firmware :

  • Using the Petoi Desktop App

  • Using the Arduino IDE

Petoi Desktop App

You can use the Firmware Uploader within the Petoi Desktop App.

Please select the correct Product type, Board version, and Serial port according to your actual use. The mode should be Standard, so press the Upgrade the Firmware button. For example, Bittle, BiBoard_V0_2, COM5 as follows:

Arduino IDE

For more details, please refer to Upload Sketch for BoBoard.

After uploading, there are two methods to activate/deactivate the camera mode:

  • Serial Monitor

    • Open the serial monitor and use the serial command "XC" to activate the camera mode.

    • Open the serial monitor and use the serial command "Xc" to deactivate the camera mode.

  • Mobile App

    • Create a mobile app command called "Activate camera" and use the code: X67

    • Create a mobile app command called "Deactivate camera" and use the code: X99

If the camera mode can't be activated, as following:

You can use the web debug GUI to upgrade the camera firmware and upload the Face Detection model.

More Application

The Petoi AI vision module also supports taking photos and transmitting images via Wi-Fi, but it needs to be installed on a MCU with more powerful computing power (such as ESP32S3, ESP32C3, etc.). For the specific development process, please refer to the wiki technical documentation:

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