Hiwonder LeArm AI is an AI open source robotic arm developed by Hiwonder, designed specifically for STEAM education. It features a high-performance ESP32 controller and supports multiple control methods, including PC, app, and wireless controller. The robot arm is equipped with 6 smart bus servos and integrates inverse kinematics algorithms, enabling precise and flexible motion. LeArm AI supports Arduino programming and offers excellent expandability with AI vision modules, voice interaction modules, and a variety of sensors. Whether it's vision recognition, target tracking, intelligent sorting, voice control, or distance measurement, LeArm AI empowers you to unlock a wide range of engaging and creative AI-powered applications.
High-Efficiency Servo
Equipped with high-torque smart digital servos, the AI robotic arm can grab objects and run smoothly.
Excellent Structure Design
Hiwonder LeArm AI robotic arm features an all-metal design, equipped with metal brackets and a bearing base, enabling it to achieve flexible rotation.
Inverse Kinematics Algorithm
We provide LeArm AI inverse kinematics analysis to allow users to better understand the working principle of the robotic arm.
Support Sensor Expansion
The Advanced Kit includes sensor modules, enabling creative functions such as AI vision interaction, AI voice control, and multi-sensor applications.
PC Software Slider Control
The PC software provides user-friendly graphical controls, allowing you to adjust servo positions with slider bars and program motions without writing any code.
PC Software Coordinate Control
Control the robotic arm's end effector to precisely move to target positions using coordinate mode, enabling efficient and accurate motion control.
App Control
Easily control the robotic arm via Bluetooth using the app, allowing for quick and convenient operation.
Wireless Controller
Enjoy real-time control of Hiwonder LeArm AI robotic arm using a PS2 wireless controller with an effective range of up to 10 meters. Designed for ease of use, it requires no programming experience to get started.
Synchronization Controller
Effortlessly control LeArm AI robotic arm wirelessly and execute movements in perfect sync using the synchronization controller.
Wireless Glove Control
Control Hiwonder robotic arm in real time using the wireless glove. With programmable responses, the arm can perform various actions based on your movements.
Color Recognition
LeArm AI accurately identifies color blocks within its field of view and uses inverse kinematics to precisely locate and lock onto the target. LeArm AI then grips the object and places it in the specified area.
Garbage Recycling
LeArm AI leverages deep learning to accurately identify various types of waste cards and can grasp and sort the corresponding objects into designated areas with precision.
Face Recognition
LeArm AI can recognize and store up to three distinct faces. Based on programming, the robotic arm will perform different preset actions for each recognized face.
Tag Recognition
LeArm AI can identify tag blocks within its field of view and precisely grasp and sort them into designated areas.
Voice Control
LeArm AI can "hear" and "understand" a variety of voice commands from users and accordingly pick up and sort colored blocks.
Voice Broadcast
With the AI voice interaction module, the LeArm AI can continuously broadcast different voice prompts, delivering seamless audio feedback.
Voice-Controlled Waste Sorting
By integrating the AI voice interaction module and the WonderMV vision module, LeArm AI can automatically identify and sort objects within its field of view based on voice commands from users.
Voice-Controlled Vision Sorting
By integrating the AI voice interaction module and the WonderMV vision module, LeArm AI can automatically identify and sort objects within its field of view based on voice commands from users.
Sound Control
LeArm AI can detect ambient sounds through a sound sensor and perform corresponding actions, enabling intelligent voice control.
Infrared Control
Equipped with an infrared obstacle avoidance sensor, LeArm AI can detect objects in front of it in real time and automatically perform actions such as grabbing and sorting.
OLED Display
With programmable capabilities, the OLED screen module can display numbers, text, graphics, and more.
Touch Control
Integrated with a high-sensitivity touch sensor, LeArm AI can detect touch status in real time and respond with appropriate actions automatically.
Ultrasonic Ranging
Using an ultrasonic sensor with an LED indicator, LeArm AI can measure the distance to objects ahead, enabling distance-based actions such as grabbing.
Acceleration Control
By continuously collecting data from the accelerometer and analyzing motion direction, LeArm AI can perform different actions accordingly.
WonderMV Vision Module Parameter
Processor
Kendryte K210
Display size
2.0 inch
Chip architecture
RISC-V architecture
Built-in function
Micropython firmware
Development environment
CanMV IDE
LED
User-defined LED light
TF card slot * 1
TF card can be inserted. 32GB TF card is recommend-ed
Fill light
Supply light for dim environ-ments, customiz-able by the user
Power supply
5.0V
Camera
2 magapixel
Working current
about 300mA
Key * 2
Costume function key
Interface
Type-C, UART, IIC
Size
58.9* 40.7* 16.2mm
Display
LCD capacitive touch screen with a resolution of 320x240
Weight
43g
WonderEcho Parameters
Size
48*24*10.5mm
Weight
10g
Supplied voltage
DC 5V
RAM capacity
60KByte
FLASH capacity
2MByte
Recognition mode
Command wake-up
Communication method
IIC Communication, connect the main controller using a 4-pin cable
Indicator status
Supports iOS and Android mobile app, PS2 controller, and PC control
Recognition range
The maximum recognition range is 5 meters in quiet conditions and 1 meter in noisy environments.
Recognition requirement
Recognition is based on predefined entries, capable of identifying up to 255 phrases or short sentences. Custom recognition words can be modified as needed.
Dimensions:
283 * 130 * 461 mm
Structure:
Full aluminum alloy body, surface sandblasted with oxide coating
