UAV Swarm Formation System
Uses ROS/PX4 and Prometheus for distributed intelligent formation. It supports line, triangle, rectangle, and circle formations, indoor and outdoor positioning, simulation, safety protection, interaction, and open APIs.
AMOVLAB Solution
UAV Laboratory Construction Solution
A complete laboratory construction program built around progressive training, full-stack coverage, and industry-university-research integration.
The solution serves vocational colleges, undergraduate programs, and graduate research teams. It builds a lifecycle teaching and research system from UAV fundamentals and single-aircraft control to advanced functions, swarm intelligence, and industry applications.
Solution Overview
A vertical pathway from basic teaching to research innovation.
The program includes curriculum systems, experimental equipment, simulation platforms, research solutions, and supporting training services. It helps universities connect foundation courses, practical experiments, research projects, competitions, graduation projects, academic papers, and industry implementation.
AMOVLAB designs the laboratory around real engineering workflows, so students and researchers can move from simulation verification to physical deployment while using the same development stack and research ecosystem.
Solution Structure
Progressive curriculum, full-stack equipment, scenario solutions, training, and open ecosystem support.
1. Progressive Curriculum System
The curriculum is divided into beginner, intermediate, and advanced stages, covering the complete process from system entry to advanced algorithm development.
- Beginner: Ubuntu, ROS, UAV software and hardware structure, and engineering foundations.
- Intermediate: PX4 + Gazebo simulation, remote-control flight practice, MAVROS, and Prometheus control development.
- Advanced: EGO-Planner path planning, SpireCV visual detection and target tracking, multi-UAV collaboration, and swarm control.
Multi-Scenario Research Solutions
Five technical platforms that help universities build distinctive research directions.
Swarm Planning and Obstacle Avoidance
Combines the SwarmFormation algorithm with LiDAR perception to support formation keeping, dynamic obstacle avoidance, real-time map building, and formation path correction.
Swarm Collaborative Search
Integrates MPC control and visual recognition for distributed area search, inter-aircraft collision avoidance, target recognition, and coordinated swarm pursuit.
Air-Ground Integrated Collaboration
Enables UAVs to identify and lock QR-code targets in the air, then transmit position data to ground vehicles for autonomous navigation and obstacle avoidance. ROS/Gazebo simulation and open code are supported.
Intelligent Inspection System
Based on AMOVLAB's SU17 UAV platform, integrating four-camera SLAM, LiDAR, gimbal payloads, and AI perception for power, construction, petrochemical, and other automated inspection tasks.
Teaching and Training Support
Systematic teaching services for university deployment.
AMOVLAB provides online courses, customized teaching, offline practical training, and technical support to help universities advance teaching and research tasks while helping students master UAV knowledge, development skills, and frontier technology applications.
- Customized technical training based on teaching priorities and research directions.
- Offline immersive AMOVLAB training camps.
- Monthly Prometheus UAV online training courses.
- Dedicated online technical Q&A groups with support from AMOVLAB engineers.
Open Ecosystem Support
Open-source resources, systematic courses, and technical communities in one learning pathway.
AMOVLAB relies on four open-source projects, Prometheus, FMT, SpireCV, and KKSwarm, to build an ecosystem covering control, planning, vision, and swarm intelligence. Combined with supporting courses and dedicated training, it creates a full-chain learning system from entry to research.
The ecosystem also includes technical forums and active communities where more than 10,000 developers accumulate knowledge, exchange ideas, and collaborate on robotics and UAV development.
Contact Us
Planning a UAV lab program?
A lab plan needs to balance equipment, courses, experiment difficulty, and future research expansion.
Useful details to include
- 01 Course level, research topics, and expected experiments
- 02 Indoor or outdoor site, safety rules, and lab capacity
- 03 Aircraft, sensors, positioning, simulation, and training needs
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