# Optimizing Terrain Mapping and Landing Site Detection for Autonomous UAVs

arXiv: https://arxiv.org/abs/2205.03522 · HTML: https://mlsanity.com/paper/2205.03522/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 6 of its 26 references that are in the map.
- First posted on arXiv 7 May 2022.

## Builds on (most cited first, 6 of 6)

- [AirSim: High-Fidelity Visual and Physical Simulation for Autonomous Vehicles](https://mlsanity.com/paper/1705.05065/) (2017)
- [Multiresolution Mapping and Informative Path Planning for UAV-based Terrain Monitoring](https://mlsanity.com/paper/1703.02854/) (2017)
- [xVIO: A Range-Visual-Inertial Odometry Framework](https://mlsanity.com/paper/2010.06677/) (2020)
- [Multi-Resolution Elevation Mapping and Safe Landing Site Detection with Applications to Planetary Rotorcraft](https://mlsanity.com/paper/2111.06271/) (2021)
- [Probabilistic RGB-D Odometry based on Points, Lines and Planes Under Depth Uncertainty](https://mlsanity.com/paper/1706.04034/) (2017)
- [Free LSD: Prior-Free Visual Landing Site Detection for Autonomous Planes](https://mlsanity.com/paper/1802.09043/) (2018)

## Built on by (most cited first, 3 of 3)

- [Federated Multi-Agent Mapping for Planetary Exploration](https://mlsanity.com/paper/2404.02289/) (2024)
- [HALO: Hazard-Aware Landing Optimization for Autonomous Systems](https://mlsanity.com/paper/2304.01583/) (2023)
- [A Multimodal Large Language Model-Driven Framework for Context-Aware UAV Emergency Landing Site Selection](https://mlsanity.com/paper/2602.01163/) (2026)

## Abstract (arXiv)

The next generation of Mars rotorcrafts requires on-board autonomous hazard avoidance landing. To this end, this work proposes a system that performs continuous multi-resolution height map reconstruction and safe landing spot detection. Structure-from-Motion measurements are aggregated in a pyramid structure using a novel Optimal Mixture of Gaussians formulation that provides a comprehensive uncertainty model. Our multiresolution pyramid is built more efficiently and accurately than past work by decoupling pyramid filling from the measurement updates of different resolutions. To detect the safest landing location, after an optimized hazard segmentation, we use a mean shift algorithm on multiple distance transform peaks to account for terrain roughness and uncertainty. The benefits of our contributions are evaluated on real and synthetic flight data.