Product Features
Deep learning based indoor service robot developing platform composed of cluster computing-artificial intelligence unit (recognition/judgment) and MCU-operation control unit
The artificial intelligence unit is composed of a computer cluster where 1-4 industrial-use high-performance NVIDIA edge super computing modules are tied with the Gigabit switch on-board enabling to develop and operate high-performance deep learning models in the robot operating system (ROS2) environment
The artificial intelligence unit provides the interfaces of Gigabit Ethernet, 802.11ac Wi-Fi, Bluetooth, USB 3.0, USB OTG, CAN, I2C, SPI, GPIO so that operating control of unmanned vehicle can be possible
The operating control unit connected to the artificial intelligence unit with CAN is composed of high-performance STM Cortex-M4 processor, motor driver, ultrasonic sensor, proximity sensor, Zigbee V3.0, and CAN transceiver to control the unmanned vehicle in real time
Camera and high-performance 360-degree Lidar are provided to realize autonomous driving service that learns and operates the surrounding situation
The 11.6-inch touch display with a resolution of 1080p is provided to realize the GUI-based intelligent service robot interface
High-performance digital microphone and speaker are provided to control the robot and check service robot condition by voice
Ultrasonic sensor and PSD sensor are provided to sense obstacles and autonomous driving of the service robot, and DC motor including an encoder is also provided to calculate the driving distance
Wi-Fi and Bluetooth communication are provided to enable remote control of the service robot through PC, smartphone, and tablet, and ZigBee V3.0 is provided to enable the platoon driving and collaboration among service robots
Enable continuous training with the large capacity battery and efficient charging system
Minimize the time required to install and set the corresponding library and framework with controlling Soda OS where Ubuntu Linux is optimized for robot operating system (ROS2) and CUDA-based deep learning framework
Supports Visual Studio Code based open integrated development environment for professional application development
Learning models of deep learning based service robot and training contents are provided
Operating Program
Hardware Specifications
Training Contents
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