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Yobot

Edge Intelligent Robot Vision Training Platform

Edge Intelligent Robot Vision Training Platform

$8,000.00 USD
$8,000.00 USD
Giảm giá Đã bán hết

Product Name: Edge Intelligent Robot Vision Teaching Kit (Upgraded Version)

Positioning: An industrial-grade AI and robotics training platform designed for universities, vocational colleges, and research laboratories.

Product Overview: This kit is an advanced artificial intelligence teaching system based on real-world industrial and daily-life application scenarios. The platform deeply integrates smart machine vision, a robotic arm, voice interaction, sensor networks, and cloud edge computing units. By assembling, debugging, and programming the hardware, students gain hands-on experience with robot applications, control principles, and system engineering, bridging the gap between theoretical knowledge and practical engineering.

▍ Core Functions

  • Intelligent Vision & Recognition: Supports image acquisition, edge detection, classification, and complex object detection.

  • Automated Material Handling: Utilizes a smart robotic arm for precise grasping, sorting, and transferring.

  • Voice & Semantic Interaction: Equipped with microphone and speaker units for advanced semantic recognition, parsing, and voice feedback.

  • Edge-Cloud Collaboration & Model Training: Enables building mainstream neural networks on computing servers for deep learning model training, followed by edge-side deployment and processing.

▍ Supported Curriculum & Lab Training Fully covers the core requirements of multiple academic disciplines with ready-to-use experiments:

  • Machine Vision Technology: Hands-on industrial vision kits for image processing and visual principles.

  • Deep Learning Technology: Server-backed neural network construction and object detection.

  • Robot Operating System (ROS): Robotic arm motion control and ROS ecosystem development.

  • Edge Computing & Machine Learning: Cloud-edge data processing and algorithm applications (regression/classification).

  • Linux OS & Python Programming: Native Linux environment and Python multi-scenario development.

  • Embedded Systems & Sensors: Environment setup and comprehensive sensor application development.

▍ Key Features & Advantages

  1. Industrial-Grade Hardware: All core units are built with industrial-grade modules, ensuring applications closely mirror real commercial and manufacturing environments.

  2. All-in-One AI Fusion: Seamlessly integrates machine vision, robotic control, deep learning frameworks, and voice technologies.

  3. From Beginner to Advanced Dev: Supports graphical programming for quick application deployment, as well as embedded code programming for complex, high-level process execution.

  4. Highly Open-Source & ROS Ready: Completely open-source application code. Includes a comprehensive ROS Software Development Kit (SDK) to accelerate research and secondary development projects.

  5. Complete Teaching Resources: Comes with detailed lab manuals, instructional videos, and extended educational materials, making course preparation effortless for educators.

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Specification parameters

1) Base/Chassis Parameters:
Motor reduction ratio: ≥1:2； Load capacity: ≥12kg； Maximum speed: ≥2.7 m/s； Body weight: ≥6 kg； Dimensions: ≥400mm*500mm； Suspension system: ≥coaxial swing suspension； Off-road wheels: ≥8 inches； Battery capacity: ≥5000mAh； Battery life: ≥6.5 hours (idle) and ≥5.5 hours (3kg load)； Motor: DC Brushed Motor； Encoder: AB-phase high-precision encoder； Features: App control supports navigation, map creation, image transmission, obstacle avoidance, and other functions； Support: Supports controllers, with reserved Usart/CAN communication control interfaces and multiple IO interfaces； Operating System: The STM32 board runs on freeRTOS ROS with Ubuntu 18.04 and Melodic

2) Host computer processing unit:
GPU: 384-core NVIDIA Volta ™ GPU with 48 Tensor Cores； CPU: A 6-core NVIDIA Carmel ARM® v8.2 64-bit processor with 6MB L2 and 4MB L3 cache； Visual Accelerator: 7-Channel VLIW Visual Processor； Deep Learning Accelerator: 2 NVDLA Engines； Video memory: 8GB； Video encoding: 2x 4K60|4x 4K30|10x 1080p60|22x 1080p30 (H.265)； Video decoding: 2x 8K30|6x 4K60|12x 4K30|22x 1080p60|44x 1080p30 (H.265)； Cameras: 2 MIPI CSI-2 D-PHY channels； Connectivity: Gigabit Ethernet, WiFi； Display: HDMI and DP； USB: 4xUSB3.1, USB2.0 Micro-B； I/O: GPIO, I2C, I2S, SPI, UART

3) Lower-level machine processing unit:
CPU: Based on STM32； Core width: ≥32 bits； Maximum clock frequency: ≥72MHz； Communication modes: Supports CAN, I2C, IrDA, LIN, SPI, UART/USART, and USB； Peripheral devices: DMA, motor control PWM, PDR, POR, PVD, PWM, temperature sensor, WDT, crystal oscillator； Input/output count: ≥51； Program memory capacity: ≥256KB； Program memory type: FLASH； RAM capacity: ≥48K； Voltage-Source (Vcc/Vdd): 2 V to 3.6 V； Oscillator type: internal

4) Laser navigation scanning unit:
Range: 0.15-12m； Scan angle: 0-360°； Range resolution: <0.5mm； Angle resolution: ≤1°； Single measurement time: ≤0.5ms； Measurement frequency: ≥4000 Hz； Scan frequency: 1-10 Hz