# Local Trajectory Planning For UAV Autonomous Landing

arXiv: https://arxiv.org/abs/2111.00495 · HTML: https://mlsanity.com/paper/2111.00495/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Oct 2021.

## Built on by (most cited first, 1 of 1)

- [From Particles to Perils: SVGD-Based Hazardous Scenario Generation for Autonomous Driving Systems Testing](https://mlsanity.com/paper/2604.18918/) (2026)

## Abstract (arXiv)

An important capability of autonomous Unmanned Aerial Vehicles (UAVs) is autonomous landing while avoiding collision with obstacles in the process. Such capability requires real-time local trajectory planning. Although trajectory-planning methods have been introduced for cases such as emergency landing, they have not been evaluated in real-life scenarios where only the surface of obstacles can be sensed and detected. We propose a novel optimization framework using a pre-planned global path and a priority map of the landing area. Several trajectory planning algorithms were implemented and evaluated in a simulator that includes a 3D urban environment, LiDAR-based obstacle-surface sensing and UAV guidance and dynamics. We show that using our proposed optimization criterion can successfully improve the landing-mission success probability while avoiding collisions with obstacles in real-time.