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Intelligent Composite Robot
Intelligent Composite Robot
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A ROS-based intelligent composite mobile robot developed on the open-source Robot Operating System (ROS) platform. The robot integrates three core modules: an autonomous mobile chassis, a multi-functional robotic arm, and a machine vision system.
The system adopts a modular design and can be equipped with various intelligent sensors, including cameras, depth cameras, ultrasonic sensors, and LiDAR, enabling it to meet the functional requirements of different application scenarios.
With capabilities such as mapping, navigation, obstacle avoidance, mobile manipulation, and visual recognition, the robot provides reliable technical verification for application scenarios including industrial inspection, logistics transportation, and intelligent manufacturing.
This robot platform can support teaching and practical training for courses such as Robotics, Autonomous Navigation Technology, ROS Application Development, Python Programming, Machine Vision Technology, and Machine Learning & Deep Learning.
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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