Hiwonder LeArm AI Desktop Robot Arm with AI Vision & Voice Interaction, Support Arduino Programming & Sensor Expansion
【ESP32 Controller & Arduino Programming】 LeArm AI is an AI open source robot arm powered by ESP32 and fully compatible with Arduino programming. It features built-in Bluetooth and multiple expansion ports, which maks it ideal for function upgrades and secondary development.
【Inverse Kinematics & Smart Bus Servos】 Equipped with 6 smart bus servos and advanced inverse kinematics algorithm, Hiwonder LeArm AI delivers precise path planning and smooth, efficient movements—perfect for tackling complex tasks.
【Versatile Sensor Expansion】 LeArm supports a wide range of sensors, including AI vision, voice module, ultrasonic, and acceleration sensors. It enables creative applications like color recognition, target tracking, face detection, voice control, and distance measurement.
【Multiple Control Options】 Control LeArm AI with an app, PC software, or wireless controller. It's incredibly easy to get started, requiring no prior experience.
【Comprehensive Learning Resources & Open Source】 Comes with 200+ tutorials, sample experiments, open source code, circuit schematics, and well-commented programs—helping users dive into AI and programming while sparking endless creativity.
Spark your creativity with LeArm AI tutorials: access source codes, video guides, schematics & 200+ projects! https://wiki.hiwonder.com/projects/LeArm_AI/en/latest/index.html.
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.
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" a variety of voice commands from the user and, based on those instructions, will pick up and sort colored blocks accordingly.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 the user.
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.
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 |
| 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 |
| Camera | 2 magapixel |
| Fill light | Supply light for dim environ-ments, customiz-able by the user |
| Power supply | 5.0V |
| TF card slot * 1 | TF card can be inserted. 32GB TF card is recommend-ed |
| 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. |
| 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 |
| Weight: | 1.24kg (Standard kit) |
| Servos: | PWM servo version: LDX-218*2 + LDX-335MG*1 + LD-1501MG*1 + LFD-06*2 |
| Bus servo version: | LX-225*2 + HTS-25L*3 + HTS-16H*1 |
| Controller: | ESP32/ STM32/ 51 Triple-in-One Controller |
| Bluetooth module: | Bluetooth 4.0 module |
| Control methods: | PS2 wireless controller / Android app / iOS app / PC software |
| Secondary development: | Open-source code & schematics provided. PC software & Android app source code are available |
| Low voltage alarm: | Supported |
| Power supply: | 7.5V 6A DC power adapter |
| Tutorials: | Comprehensive e-tutorials with images + video tutorials |
| Item | Specification |
| Product name: | LeArm open-source robotic arm |
| Dimensions: | 283 * 130 * 461 mm |
| Structure: | Full aluminum alloy body, surface sandblasted with oxide coating |
| Weight: | 1.24kg (Standard kit) |
| Servos: | PWM servo version: LDX-218*2 + LDX-335MG*1 + LD-1501MG*1 + LFD-06*2 |
| Bus servo version: | LX-225*2 + HTS-25L*3 + HTS-16H*1 |
| Controller: | ESP32/ STM32/ 51 Triple-in-One Controller |
| Bluetooth module: | Bluetooth 4.0 module |
| Control methods: | PS2 wireless controller / Android app / iOS app / PC software |
| Secondary development: | Open-source code & schematics provided. PC software & Android app source code are available |
| Low voltage alarm: | Supported |
| Power supply: | 7.5V 6A DC power adapter |
| Tutorials: | Comprehensive e-tutorials with images + video tutorials |
Questions & Answers
Have a Question?
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Where can I download the software?
Hi there, this is the link for you: https://docs.hiwonder.com/projects/LeArm_AI/en/latest/index.html
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Where is the software for the computer app to program and control the arm
Hi there, this link for you: https://docs.hiwonder.com/projects/LeArm_AI/en/latest/index.html
