# Quadrotor Autonomous Landing on Moving Platform

arXiv: https://arxiv.org/abs/2208.05201 · HTML: https://mlsanity.com/paper/2208.05201/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 10 Aug 2022.

## Built on by (most cited first, 2 of 2)

- [MagiNet: Mask-Aware Graph Imputation Network for Incomplete Traffic Data](https://mlsanity.com/paper/2406.03511/) (2024)
- [WaveLander: A Generalizable Hierarchical Control Framework for UAV Landing on Wave-Disturbed Platforms via Reinforcement Learning](https://mlsanity.com/paper/2607.01281/) (2026)

## Abstract (arXiv)

This paper introduces a quadrotor's autonomous take-off and landing system on a moving platform. The designed system addresses three challenging problems: fast pose estimation, restricted external localization, and effective obstacle avoidance. Specifically, first, we design a landing recognition and positioning system based on the AruCo marker to help the quadrotor quickly calculate the relative pose; second, we leverage a gradient-based local motion planner to generate collision-free reference trajectories rapidly for the quadrotor; third, we build an autonomous state machine that enables the quadrotor to complete its take-off, tracking and landing tasks in full autonomy; finally, we conduct experiments in simulated, real-world indoor and outdoor environments to verify the system's effectiveness and demonstrate its potential.