A single UAV can handle tasks such as photography, surveying and mapping, inspection, and delivery with a high degree of flexibility. However, in long-distance, large-area, and continuous-operation scenarios, a single-platform model quickly reaches its limits.

For example, power transmission lines often extend for dozens of kilometers. Limited by endurance, range, and communication distance, a single UAV struggles to complete wide-area coverage in one mission. In bridge inspection, a single platform also has a limited collection angle, and occluded structures can easily lead to missed defects.

When multiple UAVs, unmanned ground vehicles, unmanned surface vessels, robotic arms, and other devices execute tasks under a unified system, they can divide work by area, share information, conduct relay operations, and hand over abnormal situations. This improves efficiency and reduces the risk of mission interruption.

01

From Single-Platform Operations to Multi-Device Collaboration

Take power-line inspection as an example. A transmission line often crosses mountains, valleys, forests, and other complex environments. A single UAV must fly section by section, return for battery replacement, and take off again, so efficiency is heavily affected by endurance and link quality.

Multi-device collaboration works more like a segmented operation system. The ground station first divides the line into multiple inspection sections, then assigns those tasks to different UAVs for simultaneous execution. During flight, each device continuously transmits its position, battery level, imagery, and mission progress, while abnormal points are also consolidated on the ground.

In emergency rescue, the value of collaboration is even more obvious. High-altitude UAVs can perform rapid mapping and overall reconnaissance, low-altitude UAVs can approach key areas to confirm details, and unmanned ground vehicles can enter locations that are inconvenient or risky for personnel to deliver supplies or transfer injured people. When different devices work around the same task map, each unit knows its own responsibility and can see the status of other devices. On-site dispatch becomes clearer, while repeated search and mutual interference are reduced.

02

System Capabilities Required for Multi-Device Collaboration

Having multiple devices enter the same task area at the same time may sound straightforward, but implementation places high demands on system capability. Without a mature ground-control system, multi-UAV operations can easily suffer from route conflicts, duplicated tasks, link congestion, and unsynchronized status. Instead of improving efficiency, the operation may introduce additional risk.

Reliable multi-device collaboration usually depends on the following capabilities:

Ground station and task allocation: The system must monitor the positions, battery levels, link status, and mission progress of multiple devices at the same time, then dispatch them according to the task area, device capabilities, and field changes. If one device becomes abnormal, the system should adjust tasks promptly so the entire task chain does not stop.

Swarm control and safe separation: When multiple aircraft operate in the same airspace, route planning, takeoff and landing sequence, and obstacle-avoidance logic must be considered in advance. Devices must collaborate while maintaining safe separation, which places higher requirements on flight-control response, path planning, and real-time communication.

Communication-link assurance: When many devices are online at once, image transmission, data transmission, and control links face greater pressure. In complex environments such as mountains, under bridges, inside industrial facilities, or near tunnel entrances, link stability directly determines whether the mission can continue.

Simulation and real-platform validation: Executing complex missions directly on real platforms carries high risk. By rehearsing task routes, device division of labor, coverage areas, and conflict points in simulation, teams can identify problems before flight and reduce the cost of on-site trial and error.

03

Technology Accumulation

To meet the needs of university research and industry applications, Amu Lab has long invested in the research and development of UAV swarms and air-ground collaboration technologies. It has gradually built a technical chain covering simulation validation, mission planning, swarm control, and real-platform deployment.

Based on the Prometheus swarm framework, the ProSim simulation platform, and the air-ground collaboration suite, developers can build and validate multi-agent collaboration algorithms under a unified software architecture, then gradually migrate task logic from simulation to real equipment.

This advances multi-device collaboration from a concept demonstration into a reproducible, debuggable, and scalable engineering workflow. For university laboratories, it can support research in swarm control, path planning, and multi-agent collaboration. For industry users, it can also provide a more complete basis for system validation in inspection, rescue, logistics, and park-management scenarios.

04

Scenarios That Require Collaborative Operations

Infrastructure inspection: Transmission lines, highways, bridges, utility tunnels, and similar scenarios cover wide areas and complex environments. Single-platform operations are easily limited by endurance and viewing angle. Multiple aircraft can fly by section, collect data simultaneously, and then consolidate data centrally, improving coverage efficiency and reducing missed inspections.

Agricultural plant protection: Large-scale farmland operations require continuous coverage. Multiple agricultural UAVs can use unified route planning, zone-based operations, and relay battery swaps to reduce repeated spraying and missed spraying while improving operational consistency.

Urban low-altitude logistics: As order density increases, a single-platform round-trip model struggles to support high-frequency delivery. Multiple delivery UAVs can share route planning and dispatch systems, and when combined with ground handoff equipment, they can form a more efficient last-mile delivery network.

Emergency rescue: Disaster-site information changes quickly, terrain is complex, and personnel entry can be risky. UAVs and unmanned ground vehicles can collaborate on reconnaissance, mapping, supply delivery, and key-area rechecks, helping the command side understand field conditions faster.

05

The Low-Altitude Economy Is Entering a Stage of System Competition

In the next stage of the low-altitude economy, single-platform performance will remain important, but it can no longer determine whether a project can be implemented on its own.

Once applications truly scale, users will care about whether a system can manage many devices at the same time, operate stably in complex environments, adjust dynamically as missions change, and connect simulation validation with real-platform deployment.

This is why multi-device collaboration is receiving increasing attention. It turns UAVs from single-point tools into nodes within a low-altitude operations network, and it moves low-altitude applications from isolated flights toward continuous operations and system-based delivery.

Amu Lab will continue exploring UAV swarms, air-ground collaboration, and simulation-to-real closed-loop validation, helping more universities, research institutions, and industry users enter the development and application stage of multi-device collaboration with a lower threshold.