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Yahboom Raspberry Pi Hexapods Robot Python Programming Gesture Recognition Visual Line Following Advanced Robotics Projects for Hobbyists and Professionals (MUTO S2 with Raspberry Pi 5-8G)

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Yahboom Raspberry Pi Hexapods Robot Python Programming Gesture Recognition Visual Line Following Advanced Robotics Projects for Hobbyists and Professionals (MUTO S2 with Raspberry Pi 5-8G)

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$911.78

Delivery time 15-20 day. View detail

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Muto S2 with Jetson Nano

Muto S2 with Raspberry Pi 5-8G

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PRODUCT FEATURES

Hexapod robot 18DOF Bionic Joints: Muto S2 hexapod robot features a design with 6 legs and 18 degrees of freedom in bionic joints,Under the control of the development board Raspberry Pi or jetson nano, various bionic actions can be completed, providing exceptional stability and flexibility on various terrains, both indoors and outdoors.(There may be more 12-joint ones in the same price range on the market.)
35KG Servo Motors + All-Aluminum Alloy Structure: The 35KG high-torque serial bus servo is the core of the hexapod robot. It can accurately control the free and smooth movement of 18 joints. The aluminum alloy body allows your robot to easily travel through the jungle. It is for amateurs and professionals. Advanced Python Robotics Project
APP remote control enjoyment: The six-legged robot is equipped with a 1080p high-definition 2dof camera. Use the APP to experience the worry-free fun of wireless remote control through FPV transmission, allowing you to easily control the device without being restricted by distance or obstacles. Recommended AI Vision Multi-legged Robot Kit for Students in Electronic Programming Projects
Extended Battery Life of Over 3 Hours: With a built-in high-capacity battery, it provides continuous power for more than 3 hours, Make the six-legged robot more suitable for high-intensity crawling outdoors and provide more free crawling time for STEM coding enthusiasts, ensuring you have ample usage time without the need for frequent recharging.
AI visual recognition: Yahboom six-legged robot adopts advanced AI visual recognition technology. It can deeply learn OpenCV, Python programming, Raspberry Pi or jetson nano. The algorithm is fast and accurate. It can recognize faces, gestures, colors, and QR codes, and perform Gaze tracking. This offers a wide range of application possibilities, making it suitable for both entertainment and educational purposes.
Very important: without a development board (jetson nano or raspberry pi 5), the robot cannot move and program

Product Specifications

Product Information

Product description

AI Vision Hexapod Robot MUTO S2

Muto is an ideal companion for exploring technology, engineering and programming

Various bionic gaits

Muto is a desktop-level bionic hexapod robot with aluminum alloy body. 18PCS 35KG metal servos and exquisite structural design enable it to perform various simulation actions with amazing flexibility and diversity. With the help of Raspberry Pi or Jetson Nano as the main controller and Python3 programming, Muto can complete various functions such as color recognition, following, face tracking, QR code recognition, and visual line patrol.

18DOF motion joints

18DOF hexapod robot, all-metal aluminum alloy, sturdy and durable, able to move stably and flexibly in various environments.
Composed of 35KG bus servo, 2MP 1080 HD camera, 9900mAH large-capacity battery, professional expansion board and other high-quality accessories.
Compatible with Raspberry Pi and Jetson NANO board, using Python3 programming, and using built-in inverse kinematics algorithms to accurately control robot movement.

2DOF camera PTZ

2DOF camera PTZ, combined with OpenCV image processing, can realize AI visual functions such as face tracking, object recognition, deep learning, skeleton detection, human posture estimation, and gesture recognition.
Supports mobile APP, wireless handle, and computer web remote control, which can transmit video images in real time and experience FPV control.

Color Tracking--Muto S2 with a high frame rate camera PTZ. The system collects camera images for analysis, and combines the PID algorithm to modify the PTZ angle in real time to track colors.
Face Tracking--Muto S2 supports the HAAR face detection function, calculates the position of the face in the camera image through the PID algorithm, and controls 2DOF camera PTZ to track the face.
QR code recognition--Scan the QR code through the camera, identify the content of the QR code, and perform different actions based on the specific QR code content.
Visual tracking--The selected color is recognized through the robot's vision processing, and after visual tracking is turned on, the walking path is automatically adjusted to achieve visual tracking.
Deep learning & object detection--Using a deep learning framework to achieve efficient object recognition enables the robot to quickly and accurately detect and identify objects in the environment, and complete fixed action groups based on the identified objects.
Skeleton detection & Pose estimation--Use the poseNett computer vision library in the deep learning framework jetson-inference to detect human joint points in images. Present these joint points in the form of points and lines, and analyze the coordinate parameters of each joint point, which can realize precisely control robot movement.
Machine learning & Gesture control--By detecting the position information of finger joint points and analyzing the opening and closing status of the fingers, it can identify 1-8 different gestures. Each gesture corresponds to controlling the robot to perform eight preset actions.

servos, batteries, cameras parameters, packaging list, tutorials and dimensions

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