AI Large Model Education RobotProduct Brochure
ROS2 Robot Fleet Bundle
Multi-Vehicle Formation and Swarm Algorithm Training
Product Details
Product Overview
The Formation Package bundles multiple Lunqu chassis with a unified open-source formation framework for turnkey delivery. Instructors can immediately conduct experiments in consensus control, formation keeping, and task allocation without needing to build multi-agent communication environments from scratch.
Each vehicle maintains its own main controller and host computer, supporting both centralized scheduling validation and transformation into distributed collaboration projects. Vehicle count and wheeled configurations can be scaled to match course requirements.
Other models in the same series
Key Features
- Supports both ROS1 and ROS2; formation framework source code is open-source.
- Offer combinations such as the Ackermann Five-Car Edition, Mini Mecanum ×5 + Mini Ackermann ×5 Ten-Car Edition, and more.
- Each vehicle has an independent main controller to verify distributed collaboration and task allocation.
Typical Applications
- Multi-Robot Formation and Formation Transformation Experiment
- Cluster Task Allocation and Path Conflict Resolution
- ROS2 Distributed Communication Tutorial
Technical Specifications (12Item
- System Support
- ROS1 / ROS2: Open-source Multi-Robot Formation Framework Source Code
- Combination
- High-spec Ackermann 5-wheel version; 10-wheel version (Mini Mecanum ×5 + Mini Ackermann ×5)
- Overall Dimensions
- 266×230×196mm / 266×207×192mm / 272×189×150mm (by vehicle model)
- Curb Weight
- 2.9kg / 2.68kg / 1.8kg (varies by vehicle)
- Load Capacity
- 6kg / 6kg / 3kg (by vehicle model)
- Maximum Speed
- 1.4m/s / 1.2m/s / 1.2m/s (by vehicle model)
- Drive Motor
- MG513 Metal Gear Reduction Motor
- Encoder
- 500-wire AB GMR encoder (patent 202122109210.2)
- Control Mode
- APP, PS2 wireless controller, CAN, serial port
- Low-level Controller
- STM32F407VET6
- LiDAR
- Leishen M10P Serial Port Version
- Optional Host PC
- LubanCat 1S 4GB, Raspberry Pi 5 8GB, RDK X5 8GB, Jetson Nano 4GB