• XLeRobot Assembled Dual-Arm Robot Research Development Platform + Robot Base Expansion Kit
  • XLeRobot Assembled Dual-Arm Robot Research Development Platform + Robot Base Expansion Kit
  • XLeRobot Assembled Dual-Arm Robot Research Development Platform + Robot Base Expansion Kit

XLeRobot Assembled Dual-Arm Robot Research Development Platform + Robot Base Expansion Kit

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XLeRobot Assembled Dual-Arm Robot Research Development Platform + Robot Base Expansion Kit

Target Audience:

Young Geniuses (from 8 years old) to Top-Tier Lab Researchers
* Startups: Accelerate product prototype development using this most cost-effective, practical modular platform globally.
* DIY Enthusiasts: Build your first home service robot and give it life.
* STEM Education: Introduce cutting-edge robotic technology into middle and high school STEM classrooms and interest clubs.
* Independent College Students / Graduate Students: Affordable robotics/AI practice platform for beginners in physical robotics research.
* University Robotics Labs: Directly convert cutting-edge VLA (Visual Learning Algorithm) and RL (Reinforcement Learning) research into applications for the general public.

Pre-Purchase Information:
Currently, global robot embodiment intelligence technology is still not fully mature and cannot achieve fully autonomous household tasks. This product is a low-cost, general-purpose mobile dual-arm robotic embodiment intelligent development platform, not a plug-and-play consumer-grade product.

Before purchasing, please ensure you have basic knowledge of Linux (Ubuntu)/MacOS programming, Github, Python, and practical experience (beginners can quickly get started within a week through Bilibili tutorials or AI-assisted learning). It is recommended to first browse the official website's detailed tutorials to assess your ability to complete the related content before ordering. You can also experience simulation examples on the Maniskill simulation platform provided by XLeRobot's official website before placing an order.

If you have never used the Ubuntu system, you can refer to some tutorials on Bilibili to install Ubuntu dual system on your Windows computer.

Description:
XLeRobot 0.3.0 Dual-arm Mobile Household Robot

XLeRobot 0.3.0 is an open-source dual-arm mobile household robot designed to make embodied AI accessible with low cost and 3D-printed parts. It is ideal for demonstrations, education, and research in robotics and AI.

For detailed documentation, please visit the official project site: https://xlerobot.readthedocs.io/

(This link is authorized and recommended by the project authors. WowRobo provides the hardware kit and manufacturing support.)

Hardware Installation Guide (Video): 
https://youtu.be/upB1CEFeOlk

Packing List:
* 1 × Assembled Dual-Arm Robot (Package 1)
* 1 × Robot Base Expansion Kit (Package 2)

Packaging Details:
* Weight: 12kg



Remote Control Device:
This set does not include a remote control device. XLeRobot's official website provides example code for various control methods, including keyboard, controller for Xbox, NS Joycon, and Quest3 VR. You can also use Huggingface's official master-slave arm control system (requires an additional pair of master arms). Please select your control device based on your personal needs.

Battery and Cart:
This set does not include a battery. It is recommended to purchase a commonly available high-power portable charger or power bank that supports at least two Type-C ports (each supporting 65W fast charging) with a total power output of 140W or more. For the cart, it is recommended to directly purchase the original Raskog cart from IKEA (large version) to ensure compatibility with XLeRobot hardware.

Computing Device:
This set does not include a computing device. Ordinary developers are advised to use their own laptops for development (recommended to use an Nvidia GPU with at least a 30-series card or above for optimal performance with advanced visual algorithms, VLA inference, RL strategies, etc.). For more professional developers, you can also use standalone computing devices such as Raspberry Pi, Sweet Potato development board, Nvidia Jetson Orin, or Nvidia Jetson Thor (but you will need to independently debug the system and solve the power supply issue of the computing device).

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