Evidence-Based Landing Site Selection and Vison-Based Landing for UAVs in Unstructured Environments

TL;DR

This paper introduces a probabilistic framework for UAV landing in unstructured environments that combines decision-making under uncertainty with visual servoing for precise landing.

Contribution

It presents a novel evidence-based approach that models safety as a latent variable and integrates visual likelihoods with geometric constraints for robust landing site selection.

Findings

The approach achieves stable and cautious landings in real-world experiments.

It effectively rejects unsafe landing regions based on geometric constraints.

The method performs reliably in high-fidelity simulations.

Abstract

Autonomous landing in cluttered or unstructured environments remains a safety-critical challenge for unmanned aerial vehicles (UAVs), particularly under noisy perception caused by sensor uncertainty and platform-induced disturbances such as vibration. This paper presents an evidence-based probabilistic framework for autonomous UAV landing that explicitly separates decision-making under uncertainty from execution via visual servoing. Landing safety is modeled as a latent variable and inferred through recursive accumulation of frame-wise visual likelihoods derived from flatness, slope, and obstacle cues, yielding a temporally consistent belief map that is robust to transient perception errors. Physical feasibility is enforced through a hard geometric constraint based on the minimum required landing radius of the UAV, ensuring that undersized but visually appealing regions are rejected. The final landing site is selected using constrained maximum a posteriori estimation. Once selected, the UAV locks onto the target region using ORB feature tracking and performs precise alignment and descent via image-based visual servoing (IBVS). The proposed approach is validated through both real-world laboratory experiments and high-fidelity simulations in Nvidia Isaac Sim, demonstrating consistent, cautious, and stable landing behavior across domains.