Desktop Educational Robots-E550

Product Overview

Version Comparison

LiDAR Specification Comparison

Camera Specification Comparison

Astra RGBD Depth Camera

C70 Wide-FOV RGB Camera

Key Features

Ⅰ. AI Large Model Integration(Requires Voice Module)

01 Large Language Models (LLM)

Supports real-time access to major AI model platforms, enabling deep semantic parsing of text commands and flexible, intelligent conversational responses.

02 Large Voice Models

Powered by AI voice models, featuring real-time speech-to-text and text-to-speech conversion. Combined with on-board voice modules and speakers, intelligent interaction is more seamless than ever.

03 Large Vision Models

Leverages high-definition cameras to rapidly analyze and comprehend image content, precisely identify object categories, and provide both text and voice feedback.

04 Local Model Deployment

Supports local deployment of large models for low-latency AI inference. By eliminating cloud dependency, the autonomous decision-making capabilities of the intelligent device are significantly enhanced.

Ⅱ. AI Multi-modal Large Model Applications(Requires Voice Module)

01 AI Vision: Scene Understanding & Perception Analyzes images/videos via vision large models to identify environmental elements and relationships, providing cognitive feedback.

02 AI Recognition: Object Tracking Locks onto targets through vision model analysis to perform real-time dynamic tracking.

03 AI Interaction: Color-Aware Line Following Uses Large Language Models (LLM) to identify color information for interaction, precisely sensing lines for path following.

04 Flexible Chassis Control AI-empowered chassis control with LiDAR-based emergency stop capabilities for safe and intelligent maneuvering.

05 AI Interaction: LiDAR Tracking LLM-activated LiDAR tracking for seamless transitions between convenient control and precision tracking.

06 Built-in RAG + Dual-Model Inference Architecture Retrieves semantic fragments from knowledge bases; LLMs handle task decomposition and step planning, while multi-modal models convert instructions into executable Vision-Action closed-loop commands.

07 Voice Wake-up & Interruption Support Allows voice commands to interrupt ongoing operations to receive and process new dialogue instructions.

Ⅲ. Embodied AI SLAM Mapping & Semantic Navigation

01 AI Multi-modal Large Model + Semantic Control Mapping

Understands semantics through AI multi-modal large models. Once mapping is activated, the robot is controlled via semantic commands to scan and save maps of the area.

02 AI Multi-modal Large Model + Semantic Navigation

Set semantic coordinate files within the pre-built map. During navigation, these are loaded automatically; the robot understands semantic meanings and assigns navigation target points accordingly.

03 AI Multi-modal Large Model + Voice Semantic Labeling

Add new semantic coordinate labels via voice dialogue during navigation without pre-writing configuration files. Low environmental requirements with high labeling flexibility.

04 AI Multi-modal Large Model + Full-Function Combined Application

Leveraging AI multi-modal voice interaction, all robot functions can be combined without relying on specific environment setups. Supports auto-start of interactive nodes, allowing users to master ROS functions with zero coding for a quick start.