Zevon EduBot
  • ROS Bionic Corgi Robot Dog with AI Vision SLAM Navigation Intelligent Programming Powered by Raspberry Pi 4B
  • ROS Bionic Corgi Robot Dog with AI Vision SLAM Navigation Intelligent Programming Powered by Raspberry Pi 4B
  • ROS Bionic Corgi Robot Dog with AI Vision SLAM Navigation Intelligent Programming Powered by Raspberry Pi 4B
  • ROS Bionic Corgi Robot Dog with AI Vision SLAM Navigation Intelligent Programming Powered by Raspberry Pi 4B
  • ROS Bionic Corgi Robot Dog with AI Vision SLAM Navigation Intelligent Programming Powered by Raspberry Pi 4B
  • ROS Bionic Corgi Robot Dog with AI Vision SLAM Navigation Intelligent Programming Powered by Raspberry Pi 4B
  • ROS Bionic Corgi Robot Dog with AI Vision SLAM Navigation Intelligent Programming Powered by Raspberry Pi 4B
  • ROS Bionic Corgi Robot Dog with AI Vision SLAM Navigation Intelligent Programming Powered by Raspberry Pi 4B
  • ROS Bionic Corgi Robot Dog with AI Vision SLAM Navigation Intelligent Programming Powered by Raspberry Pi 4B
  • ROS Bionic Corgi Robot Dog with AI Vision SLAM Navigation Intelligent Programming Powered by Raspberry Pi 4B

ROS Bionic Corgi Robot Dog with AI Vision SLAM Navigation Intelligent Programming Powered by Raspberry Pi 4B

ROS Bionic Corgi Robot Dog powered by Raspberry Pi 4B with AI vision, SLAM navigation, and intelligent programming. Ideal for robotics research, education, and AI development.

Model:
Standard version
Advanced version
Pro version

USD 604.5

contact shop

Corgi ROS SLAM mapping and navigation 

quadruped robot dog

------------------------------------------------

Laser SLAM Mapping and Navigation | Visual SLAM Mapping and Navigation | ROS Operating System | AI Machine Vision


Product Features

Feature-rich, fun and easy to use

ROS Operating System
An open-source meta-operating system that provides the services an operating system should offer.

OpenCV
is a mainstream deep learning framework that can meet the needs of most artificial intelligence projects.

Mapping and Navigation
Built-in mapping and navigation algorithm package, enabling autonomous obstacle avoidance during navigation.

Built-in IMU
The built-in IMU sensor allows for real-time adjustment of the aircraft's attitude.

Serial Bus Servos
13 high-performance serial bus servos, powerful and efficient

Python programming
A mainstream programming language with numerous developer communities.

Raspberry Pi 4B: The Raspberry Pi 4B offers powerful performance, resulting in faster and smoother operation.

TOF LiDAR
Can meet the needs of ROSSLAM function development for mapping and navigation, path planning, etc.

3D reality mapping can be achieved in conjunction with a depth camera.


RASPBERRYPI (built-in Raspberry Pi 4B)

AI performance has been greatly improved, and image and video transmission is smoother.


CPU
64-bit 1.5GHz quad-core
28nm process)

GPU
Broadcom VideoCore VI
@ 500MHZ


PACKAGE DIFFERENCES

Standard version 

(meets most development needs)

Advanced version
(Includes RGB camera)

Professional version 

(including depth camera)

RGB Webcam (Advanced Version)

Depth Camera (Pro Version)

A high-definition RGB monocular camera, combined with a robot dog gimbal for rotation, enables AI vision functions in various scenarios.

The depth camera not only realizes all the AI vision functions of an RGB camera, but also enables advanced features such as depth image data processing, 3D vision mapping and navigation.


FUNCTIONAL DIFFERENCES

Features

Standard Edition

Advanced Edition

Professional Edition

Wi-Fi real-time video

Android mobile app remote control

Fun actions

Custom actions

Attitude angle control

Camera gimbal rotation

Wireless controller control

SLAM mapping and navigation

Body self-balancing

KCF target tracking

Face recognition

Edge recognition

Aruco augmented reality

Gesture recognition

QR code recognition

RTABMAP visual SLAM


ROS Robot Operating System

A Leading Global Robot Communication Framework

ROS (Robot Operating System) is an open-source meta-operating system for robots.

It provides operating system-like services, including hardware abstraction, low-level driver management, execution of shared functions, inter-program message passing, and program distribution package management. Its primary goal is to support code reuse for robot research and development.

                                                                        Application Functions               Ecosystem                      Development Tools        Communication Mechanisms


Laser SLAM mapping and navigation

The CorgiROS robotic dog is equipped with a TOF LiDAR sensor on its back, enabling real-time 360° scanning of the surrounding environment. This allows for laser SLAM functions such as mapping and navigation, path planning, dynamic obstacle avoidance, and simultaneous localization. Users can also customize the system with their own AI features, enjoying even more technological fun!

①LiDAR Mapping and Navigation       
Supports mapping algorithms such as Gmapping, Karto, and Hector, and supports path planning, fixed-point navigation, and multi-point navigation.

②Multi-point navigation and dynamic obstacle avoidance
The lidar can detect the surrounding environment in real time, dynamically avoid obstacles during navigation, and replan the path after detecting an obstacle.


Equipped with a 3D depth camera

(Depth camera package)

Equipped with an Orbbec series depth camera, the head not only enables all the AI vision functions of an RGB camera, but also allows for the development of more depth vision functions such as depth image data processing and RTAB 3D visual mapping.

Model number

DaBai DCW

Depth processing chip

MX6000

Depth accuracy

1.0%@1m

Camera operating principle

Binocular structure lighting

Operating range

0.2m-2.5m

Data transmission

Type-C

①RTABSLAM 3D Vision Mapping and Navigation
Utilizing the RTABSLAM algorithm, it fuses visual and radar data to construct a 3D color map. The robot can autonomously navigate and avoid obstacles within this map, supporting global relocalization and autonomous localization functions.

②Depth Image Data and Point Cloud Images
Depth images, color images, and point cloud data from the camera can be obtained through the corresponding API.

③AI visual recognition function gameplay
The head can be equipped with either an RGB camera or a depth camera, and uses an integrated machine vision library to freely develop AI vision functions.

Face recognition
Using the CascadeClassifier algorithm, it can quickly identify faces when they appear within the field of view.

Edge Detection
The hexapod bionic robot uses various detection algorithms to output real-time edge detection results.

Aruco Augmented Reality
Supports dynamic detection and tracking of QR code AR tags,and can obtain the pose and coordinates of the QR code tags.

Gesture Recognition
OpenCV enables real-time gesture detection,and allows control of a hexapod bionic robot to perform corresponding actions.

KCF Object Tracking
Based on the image-based KCF correlation filtering algorithm, it can select any object in an image to achieve target tracking.

Visual gimbal
The biomimetic hexapod robot's head has a 1-DOF (degree of freedom) rotating gimbal, enabling visual tracking of objects.

Radar tracking
The hexapod bionic robot uses lidar to scan moving objects in front of it to track targets.

Group Control Formation
Multiple biomimetic hexapod robots can form different formations to achieve multi-robot group control.

QR code recognition
Through image processing and analysis, the biomimetic hexapod robot can perform corresponding actions after recognizing motion commands.

Color Recognition
Supports multiple color selections; the bionic hexapod robot's head will track objects of the corresponding color in real time.



Diverse control methods



Little R Technology's six-legged bionic robot supports multiple control methods (PC and gamepad).The gamepad allows control of the robot's movement in all directions. The PC version can be used with our provided virtual machine development environment to implement advanced SLAM functions such as visual SLAM mapping and navigation

1.Mobile phone control

2.Computer control

3.Handle control


13-DOF joints

The Corg ROS robot dog's body is made of aluminum alloy, making it lightweight and high-strength. It incorporates 13 high-performance serial bus gyroscopes, connecting the elbow, shoulder, and chest joints of each leg. Using inverse kinematics algorithms, the robot dog can precisely perform complex movements, ensuring overall smoothness and closely mimicking the movement postures of a real animal.


The controller sends control 

commands to the devices via the port. Each device can be assigned a unique ID number to match different application scenarios.

Employing an all-metal gear set, it boasts superior characteristics such as high precision, excellent meshing, and wear resistance, resulting in a 

service life far exceeding that of similar rubber geared servos.

The main shaft and the secondary shaft work together, and the joints are rotated by the power output of the servo motor, so that the robot dog's joints can move stably.



XR-S300 Dual-Axis Serial Bus Servo

300° angle controllable; joint angle readback.


Cool and durable. Clear wiring, small size, powerful.

High precision and high torque; stall torque 2.3 kg·cm

Responds quickly; Rotation speed: 0.108 seconds/60°


The biomimetic gait is incredibly lifelike.

The app features a variety of fun actions that use inverse kinematics algorithms to realistically simulate canine movements such as walking, sitting, spinning, and leaning forward.

1.Standing

2.Sit down

3.Bending over

4. Tilt


Built-in IMU attitude sensor

By using inverse kinematics algorithms, the system vividly simulates the walking, squatting, rotating, and crouching movements of hexapods, thereby adapting to various complex road surfaces and achieving all-terrain driving.



Parameter

Corgi ROS SLAM Intelligent Quadruped Robot Dog Size

DaBai Depth Camera Size                                                         RGB Camera Size

Corgi ROS SLAM Intelligent Quadruped Robot Dog Specifications

ROS Main Controller

Raspberry Pi 4B4G Quad-core Cortex-A72 64-bit SOC

Underlying Main Controller

Dual Harvard architecture Xtensa LX6 CPU, 240MHz clock speed

Total Degrees of Freedom

13 ADOs (Domains of Freedom)

Main Control System

FreeRTOS, Ubuntu

Body Material

Aluminum alloy construction

Interfaces

UART/SPI/I2C/GPIO

Power Supply Voltage

DC 8.4V

Battery Capacity

3000mAh battery

Battery Life

≤40 minutes of normal operation

Function Cameras

480P wide-angle camera

RGB Cameras

480P wide-angle camera 2MP (Advanced version)

Depth Cameras

Orbbec DaBai 3D depth camera (Professional version)

LiDAR

Orida MS200

Servo Models

XR-S300 high-performance serial bus servo

Control Distance

<20 meters (AP mode)

Control Terminal

Suitable for mobile phones, tablets, gamepads, PCs

Programming Tools

Python/C++

Product Dimensions

232*191*169mm (Standard version)

Product Weight

885G (Standard version - net weight)

MS200 LiDAR

Product Model

MS200

Distance Range

0.02m~12.0m

Measurement Accuracy

40mm

Rotation Speed

Configurable to 5~15Hz (rpm)

Angle Resolution

0.8°@10Hz 0.4@5Hz

Fast Scan Measurement

Spot frequency 4.5kHz

Distance Accuracy

Less than 20mm

Operating Temperature

-10°C~50°C

Product Dimensions

37.7*37.5*32.5mm


PACKAGE LIST

1.Corgi Intelligent Quadruped Robot Dog   2.Instruction Manual   3.Packaging box  4.ROS main control module 5.RGB Webcam (Advanced Version)
6.Depth Camera (Pro Version)  7.Gamepad  8.Charger  9.Warranty Car


Supplier Information

Email:ZevonEduBot@ttbridge.com

Tel:17734786008

Recommended products

Bionic robot dog, open source HarmonyOS, Master Brother robot, AI intelligent mechanical dog

Bionic robot dog, open-source HarmonyOS, Master Brother robot, AI intelligent mechanical dog, voice, STEAM education, programming.

collect:0

AI-powered vision-based quadrupedal bionic robot dog, intelligent programmable robot,

AI-powered vision-based quadrupedal bionic robot dog, intelligent programmable robot, large-scale model using ROS and Raspberry Pi, Python.

collect:0