PuppyPi: Hiwonder Quadruped Robot with AI Vision Powered by Raspberry Pi ROS Open Source Robot Dog - Advanced Kit

• This is PuppyPi advanced kit (Raspberry Pi included)
• Support Gazebo simulation
• Powered by Raspberry Pi 4B 4GB and based on ROS
• Capable of gait planning and adopt linkage kinematics
• Possess machine vision and work with OpenCV

NOTE: PuppyPi has standard and advanced kits available and this version is PuppyPi advanced kit. If you're interested in the STANDARD KIT, please visit the link BELOW for the detailed information:

PuppyPi Standard Kit: https://www.robotshop.com/en/puppypi-hiwonder-quadruped-robot-with-ai-vision-powered-by-raspberry-pi-ros-open-source-robot-dog-standard-kit.html

Tutorial Link for PuppyPi: https://drive.google.com/drive/folders/1sgG2CQcXimtivb-J_ILMTr9niWKPPdqN?usp=sharing

Powered by Raspberry Pi 4B 4GB, PuppyPi is an AI vision quadruped robot. It is made of aluminium alloy and loaded with 8 powerful coreless servos. Linkage mechanism on its leg attributes to flexible and diverse actions and enables it to walk, step up and down stair, etc. It owns first person vision for realizing more interesting AI games, including target tracking, face detection, line following, auto climbing and so on.

PuppyPi is based on ROS (robot operating system) and supports Gazebo simulation. It serves as a great platform for you to learn and verify machine vision, robot kinematics, quadruped gait controlling and other algorithms. Besides, ample tutorials and open-source codes will help you quickly get started!

-Realistic Bionic Appearance

Linkage Mechanism, Efficient Movement: PuppyPi’s legs employ a linkage mechanism to increase the angular velocity of its lower legs. The independent movement of different parts of the leg contributes to a greater rotation range.

Aluminium Alloy Body with Perfect Structure: Made of aluminium alloy and equipped with metal bearings on joints, PuppyPi features light weight and high strength. Compact and flexible body lets it show talents even on the desk.

-Gait Planning, Free Adjustmen

Walk, Amble and Trot gaits can be realized through adjusting touchdown time, lift time and lifted height of each leg as well as the speed of switching front legs and hind legs.

-Inverse Kinematics, Linkage Mechanism

Through inputting the coordinate of the end of the leg into the visual PC software, the servo angle can be calculated by its inner processor so as to design cool actions.

-Speed, Height and Inclination Adjustment

PuppyPi's its height and inclination can also be adjusted to make it turn as walking.

-Intelligent Self-balancing

The built-in IMU sensor can monitor PuppyPi’ s posture in real-time to adjust its joints to balance the body.

-AI Vision, Unlimited Creativity

With built-in HD wide-angle camera of 100W pixel, PuppyPi is capable of recognizing and locating different targets to realize line following, crossing obstacle, face detection, ball shooting, color tracking, tag recognition and other creative AI games.

-Support APP Control, FPV Image Feedback

Android and iOS mobile APP are available. Via the APP, you can remotely control the robot and view what the robot sees.

-Support Sensor Expansion, Create More Functions

PuppyPi is compatible with MP3 module, touch sensor, dot matrix display, ultrasonic sensor and other modules making it possible to build more creative AI projects.

-ROS Robot Operating System

ROS is an open-source meta operating system for robots. It provides some basic services, such as hardware abstraction, low-level device control, implementation of commonly used functionality, message-passing between processes, and package management.

And it also offers the tools and library functions needed to obtain, compile, write, and run code across computers. It aims at providing code reuse support for robotics research and development.

-Support Gazebo Simulation

PuppyPi adopts ROS framework and supports Gazebo simulation. Gazebo brings a fresh approach for you to control PuppyPi and verify the algorithm in simulated environment, which reduces experimental requirements and improves efficiency.