Landing on a moving platform is a representative task for testing whether a UAV can progress from fixed-point landing to dynamic coordination.

The platform remains in motion and may accelerate or turn, while the landing area is limited. Changes in viewing angle, lighting, wind disturbances and communication latency can all affect tracking and control accuracy.

Conventional fixed-point landing assumes that the target position does not change, making it difficult to handle moving targets directly. The UAV must continuously estimate the platform's state and adjust its approach trajectory according to the platform's motion.

By using onboard vision or data from multiple sensors for platform recognition, relative localization and trajectory prediction, the UAV can autonomously select a landing window and align with the moving platform.

How can a UAV track a continuously moving platform reliably, align precisely, and autonomously abort the landing when conditions become unsafe?

This is the focus of our latest innovation topic: Autonomous UAV Landing on Moving Platforms. It explores the integration of dynamic target perception, relative navigation and safe landing.

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Challenge Topic Overview

Autonomous UAV Landing on Moving Platforms

This topic focuses on moving platforms such as vehicles, unmanned ground vehicles and vessels. It explores how UAVs can autonomously detect targets, maintain continuous tracking, predict motion, approach and align, and land safely.

Core tasks:

Define the moving platform's route, speed and turning behavior, and specify the landing area and safety boundaries to create repeatable test scenarios;

Autonomously recognize and continuously track the moving platform, estimating relative position, velocity and heading, as well as suitable landing opportunities;

Complete the approach, alignment, descent and touchdown confirmation, and autonomously abort, go around or retry when conditions are unsafe.

The UAV needs the following capabilities:

Moving-platform detection, recognition and continuous tracking;

Relative position, attitude and velocity estimation;

Platform trajectory prediction and time synchronization;

Approach guidance, trajectory planning and alignment control;

Compensation for wind disturbances, latency and platform maneuvers;

Safe aborts, go-arounds, landing confirmation and performance evaluation.

The ultimate goal is to move from manual, remote-controlled alignment and landing to autonomous tracking of a moving platform and safe touchdown.

Challenge Objectives

Six technical directions form a complete closed loop, from target detection and relative navigation to safe landing on a moving platform.

Moving-Platform Detection and Tracking

Identify the landing platform using an onboard camera or other sensors, and maintain continuous, stable tracking despite changes in scale, viewing angle and background.

Technical directions:

Object detection | Visual markers | Continuous tracking

Relative Localization and State Estimation

Estimate the UAV's position, attitude, velocity and heading relative to the platform, providing real-time state information for approach guidance and descent control.

Technical directions:

Pose estimation | Sensor fusion | State filtering

Motion Prediction and Landing-Point Planning

Estimate the platform's short-term trajectory from its motion history. Select the landing time and target touchdown point by considering platform speed, turning trends and safety boundaries.

Technical directions:

Trajectory prediction | Temporal alignment | Landing-point planning

Intercept Approach and Alignment Guidance

Plan pursuit and approach trajectories, gradually match the platform's speed and heading, and move into a stable descent position while maintaining safe separation.

Technical directions:

Intercept guidance | Speed matching | Trajectory control

Precision Descent and Landing Confirmation

Maintain alignment with the landing area despite relative motion, wind disturbances and image jitter. Complete a gentle touchdown, stop the propellers and confirm the landed state.

Technical directions:

Visual servoing | Disturbance compensation | Touchdown detection

Safety Strategies and Performance Evaluation

Test different platform speeds, acceleration and deceleration, turns, brief occlusions and wind disturbances to validate autonomous abort, go-around, retry and emergency-response strategies.

Technical directions:

Safe aborts | Go-arounds and retries | Metric-based evaluation

Application Scenarios

Autonomous landing on moving platforms is not only a precision flight-control challenge; it also supports several real-world applications involving cooperation among unmanned systems.

Vehicle-Based UAV Operations

After completing a mission, the UAV autonomously returns to a moving vehicle, reducing stops and waiting time while extending the range of continuous operations.

Recovery on Moving Maritime Platforms

Recover the UAV on a vessel's deck or an unmanned surface vessel to support maritime inspection, search and environmental monitoring.

Automated Recharging and Mission Continuation

Land on a mobile charging platform to recharge or replace the battery, then resume inspection and delivery missions.

Heterogeneous Robot Coordination

Validate shared perception, mission handoffs and dynamic coordination among UAVs, unmanned ground vehicles and unmanned surface vessels.

Suggested validation outcomes:

Have the moving platform travel straight, accelerate, decelerate and turn at different speeds while the UAV uses onboard perception to detect, track, approach, align with and land on it. Report metrics such as landing success rate, touchdown error, mission duration, number of go-arounds and safe-abort rate.

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Flying Robot Innovation and Creation Challenge

Advancing flying robots requires more validation in real-world scenarios. An innovative idea can become a valuable product only through development, testing and application validation.

To enable more developers to take part, the 2026-2027 Flying Robot Innovation and Creation Challenge is now officially open.

Open to universities, research institutes, technology companies, developer teams and flying-robot enthusiasts, the competition provides an innovation platform that brings together technical learning, project development, scenario-based validation and the presentation of results.

Participating teams can develop projects using the FlyCore Integrated Control System for Flying Robots. From concept design and system setup to scenario-based validation and competition demonstrations, teams can create their own innovative flying-robot projects.

The competition will also run regular flying-robot development boot camps covering system setup, technology development and hands-on projects, providing participating teams with opportunities to learn, exchange ideas and advance their projects.

New Innovation Topics to Guide Exploration

To help participating teams move quickly into hands-on development, the challenge will continue to release a series of innovation topics.

Each topic will combine flying-robot technologies with real-world application scenarios, providing developers with project ideas and references.

Developers can conduct research based on the recommended topics or extend them in new directions according to their own interests.

Turning a technical idea into a flying robot that can complete real tasks is precisely the innovation process this challenge aims to encourage.

 

03

Build with FlyCore and Compete for a Million in Innovation Funding

The FlyCore Integrated Control System for Flying Robots provides an integrated development foundation, from flight control and localization and navigation to mission development.

FlyCore integrates core capabilities including flight control, mapping and localization, recognition and planning, and sensor integration. It creates a complete perception-localization-planning-control loop, enabling developers to quickly build flying-robot platforms, validate algorithms and explore applications.

With FlyCore, participating teams can quickly complete concept design, feature development and scenario-based validation, turning innovative ideas into robots that can actually fly and perform tasks.

With FlyCore, teams can:

✓ Quickly build flying-robot platforms
✓ Validate algorithms and develop features
✓ Complete testing in real-world scenarios
✓ Present their projects in the challenge competition

Let your ideas take flight and bring innovation into real-world applications.

This year's challenge has established a dedicated annual incentive fund totaling one million and is seeking innovative flying-robot projects with real-world application value and product potential. In addition to cash awards, outstanding projects will receive support in technical guidance, prototype refinement, engineering validation, supply chains and marketing. Exceptional projects may also enter a product co-development program and gain access to industry resources, startup incubation or strategic investment support.