Description
From the brand



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SLAM Lidar Series
Desktop robot arm controlled by a virtual machine: Dofbot-SE robot arm uses a virtual machine as the main controller and does not rely on the expensive RaspberryPi jetson nano. It also implements complex grasping tasks such as custom model training, garbage classification, and gesture recognition. take action (VM Software Not Support MAC) Yahboom only provide Windows version.
6DOF intelligent serial bus servo robot arm: The robot body of the robot arm contains 6 bus servos that support readback of position and status information. The servo has built-in metal gears, high-precision potentiometers, anti-reverse connection interfaces, and can be cascaded. control. As a key accessory of the robotic arm, the powerful servo system can ensure accurate movement of the robotic arm and increase its service life, allowing it to easily grab objects weighing 200g-500g.
Diversity of control methods: The robot kit can be controlled through the standard wireless handle, mobile APP and computer mouse in the kit. Multiple operation methods can be used for various projects and learning, bringing more creative possibilities and fun.
Creative function development: the camera and the robotic arm are combined into one. The camera is responsible for AI recognition work, and the robotic arm is responsible for command output operations. It realizes inverse kinematics algorithm by controlling each joint, color recognition, tracking and grabbing, gestures and faces. Recognition tracking, MediaPipe machine learning, action group copying, chess playing, garbage classification and a series of complex actions
High-quality structure and high-quality after-sales service team: The robotic arm uses high-quality aluminum alloy and industrial-grade bearings, which can be used and learned endlessly. Yahboom develops Python source code for Dofbot SE, with 151 courses, from basic to advanced learning, and technical support to protect you.
Complete package, no need to prepare expensive development board master













MediaHouse –
Educational robot with serious capabilities
I purchased the this robot arm mainly for AI and robotics experimentation, and I’m genuinely impressed with what Yahboom has delivered here. This is not just a toy- it’s a serious, programmable desktop robot with excellent learning potential and hardware design.The arm uses 6 intelligent serial bus servos with metal gears and status feedback- a huge step up from PWM servos. The movement is precise, smooth, and strong enough to lift up to 500g. The all-metal structure and industrial bearings feel solid and professional, not like the plastic kits I’ve used before.One of the best parts is that it doesn’t require a Raspberry Pi or Jetson Nano. It runs off a Windows-based virtual machine, which saves money and simplifies setup. However, be aware that Mac is not supported, so you’ll need a Windows PC or laptop to get it running.This robot really shines with its built-in camera and AI vision functions. Using the included software and machine learning tools (like MediaPipe), I was able to set up garbage classification, gesture control, and basic object recognition. You can literally make it play chess or do color-based sorting with the right training.The inclusion of a wireless gamepad, mobile app, and PC mouse support makes testing and demoing different modes super easy. This flexibility helps in both learning and developing new interaction methods.Yahboom provides an incredible set of 151 courses, written clearly with examples in Python. They walk you through everything from basic servo movement to AI tasks. Their technical support has been very responsive, especially when I hit some snags with the virtual machine.
ninfee –
Nice robot for education
It’s fun to make it work! It took some time to download and install the virtual machine and required packages, but it worth the time and effort. We were able to control the robot arm using simple python codes. and also the AI modules are good to explore. I tried ran yolo object detection with it, worked very well.