The V650 Semi-Outdoor ROS Navigation Platform is a highly versatile and robust robotic chassis, engineered for both indoor and semi-outdoor autonomous navigation tasks. It comes with powerful controller options and comprehensive ROS integration, making it an ideal platform for advanced AI and robotics research, education, and development.
Key Features
- Intelligent Dual-Wheel Differential Base: This design ensures high mobility and stability, crucial for various navigation tasks and ideal for ROS-based motion control research. The encoder motors provide precise odometry and smooth turning capabilities.
- Supports AI Computing with Orin NX GPU: A high-performance platform that enables real-time object detection, semantic mapping, and advanced autonomous planning, with options for Raspberry Pi 5, NVIDIA Jetson Orin NX, or Xavier NX (optional RDK X5 AI computer).
- Full ROS and SLAM Integration: Equipped with Ubuntu 20.04/22.04 and pre-installed ROS1 Noetic or ROS2 Humble. It includes the ROS Navigation Stack, Cartographer SLAM, and AMCL for real-time localization and mapping.
- Semi-Outdoor Rugged Design: Features an IP54-rated CNC machined aluminum alloy chassis with reinforced mounts, providing dust and splash resistance. This makes it suitable for complex environments such as labs, corridors, open workshops, and semi-outdoor campus navigation.
- Flexible Expansion and Customization: Offers modular I/O interfaces including USB 3.0, UART, I2C, CAN, Ethernet, Wi-Fi, and Bluetooth (optional 4G/5G data module) for integrating various sensors like LiDAR, depth cameras, GPS, and other AI sensors to meet diverse research requirements.
- Simulation and Visualization Support: Compatible with Gazebo for simulation, Rviz for visualization, and Python SDKs, facilitating academic coursework, software-in-loop testing, and autonomous navigation interface development.
- Ready for Autonomous Navigation Experiments: Comes with pre-configured ROS packages and thoroughly tested hardware, allowing for immediate setup and deployment in research and teaching environments.
Technical Specifications
| Feature | Detail |
|---|---|
| Product Name | V650 Two-Wheel Differential Drive ROS Intelligent Robot Chassis |
| Model | V650 Semi-Outdoor ROS Navigation Platform |
| Main Controller | Raspberry Pi 5 (8 GB) / NVIDIA Jetson Orin NX / Xavier NX (optional RDK X5 AI computer) |
| Operating System | Ubuntu 20.04 / 22.04 (pre-installed with ROS1 Noetic or ROS2 Humble for SLAM and Navigation) |
| Drive Architecture | Two-wheel differential drive with rear casters, encoder motors |
| Motor Controller | Dual-channel PID regulation with PWM speed control and feedback to ROS topic nodes |
| Sensors | 2D LiDAR, 9-axis IMU, optional RGB or Depth Camera |
| Positioning | Optional GPS or RTK module extension |
| Navigation System | ROS Navigation Stack (AMCL, Move Base, DWA, Cartographer, GMapping SLAM) |
| AI Functions | Vision-based object recognition, line-tracking navigation, sensor fusion path control |
| Chassis Material | CNC machined aluminum alloy, shock resistant, IP54 rated design |
| Power System | 12–24 V lithium battery pack with BMS protection and charging interface |
| Connectivity | USB 3.0, UART, I2C, CAN, Ethernet, Wi-Fi, Bluetooth (optional 4G/5G data module) |
| Dimensions | Approx. 500 × 400 × 250 mm |
| Payload Capacity | Up to 20 kg |
| Max Speed | 1.8 m/s |
| Software Support | Rviz visualization, Gazebo simulation, Autonomous navigation interface, Web remote control |
| Programming Languages | Python / C++ with ROS API support |
| Applications | SLAM and navigation research, AI and autonomous control education, Semi-outdoor campus patrol and data collection, Mobile sensor system research |
| Certifications | CE / RoHS / Compliant for Scientific Research and STEM Education |