Optimizing Terrain Mapping and Landing Site Detection for Autonomous UAVs

TL;DR

This paper presents a novel system for autonomous hazard avoidance and safe landing site detection for UAVs on Mars, utilizing multi-resolution mapping, uncertainty modeling, and hazard segmentation to improve landing safety.

Contribution

Introduces a new multi-resolution height map reconstruction method with an uncertainty model and a hazard detection approach for autonomous UAV landing.

Findings

More accurate and efficient height map reconstruction.

Effective hazard segmentation and safe landing spot detection.

Validated on real and synthetic flight data.

Abstract

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.