
Manufacturer part no. 4010100029
Listed by elephantrobotics at €718.55. Delivered to France, including shipping, VAT and any customs duty, it comes to about €880.26. Prices last checked on 2026-09-15.
Delivered cost is an estimate for a single item shipped to mainland France; the seller's checkout is authoritative.
| Item | €718.55 |
|---|---|
| Shipping | €15.00 |
| VAT (20%) | €146.71 |
| Total delivered | €880.26 |
Estimate for a single item delivered to mainland France, shipped from outside the EU: customs duty and clearance fees may apply and are charged by the carrier.
| Weight | 6 kg |
The myCobot 280 RDK X5 is built with the RDK OS operating system and equipped with the D-Robotics RDK X5 Robot Developer Kit. It offers up to 10 TOPS of computing power and supports various complex models, including Transformer, RWKV, Occupancy, Stereo Perception, and the latest algorithms. This enables rapid deployment of intelligent applications. With a focus on intelligent computing and robotics applications, it provides rich interfaces and exceptional ease of use. Support for Multiple Open-Source Vision and Large Language Models Large Language Models (LLMs) It supports the deployment and efficient operation of large language models (LLMs) based on Transformer and RWKV, such as LLaMA, RWKV V4 0.5B, Qwen2-0.5B, CLIP, and other vision-language models. It enables features like image-text search and language interaction on the RDK X5. YOLO-World Vision It supports edge-side open vocabulary detection models, combining language and visual features, offering strong generalization capabilities. It runs efficiently on the RDK X5 and can address the long-tail problem in robotics. Mobile SAM It supports lightweight, general-purpose segment-ation networks on the edge side, utilizing the combination of prompts and images to achieve universal object segmentation. It runs efficiently on the RDK X5 and, combined with YOLO-World, enables pixel-level localization of obstacles in images. PRODUCT VIDEO Compatible with RDK AI Kit It integrates seven visual algorithms and supports the local deployment of the Deepseek large model. It covers applications such as object recognition with YOLOv8, waste classification detection, ArUco code recognition for palletizing, and OCR text recognition and extraction. From image feature extraction to neural network deployment, it builds a complete algorithm application-engineering practice workflow. With Python code implementation for neural network deployment, it enables quick mastery of AI vision algorithm development and robot collaboration capabi