Enhancing UAV Search under Occlusion using Next Best View Planning

TL;DR

This paper introduces a novel next best view planning strategy for UAVs to improve search effectiveness in occluded environments like dense forests, using heuristics to optimize camera viewpoints and enhance object detection.

Contribution

It proposes two new optimization heuristics for next best view planning, significantly improving UAV search performance in occluded terrains compared to existing methods.

Findings

Visibility heuristic detects over 90% of hidden objects in simulations.

Visibility heuristic achieves 10% higher detection rates than geometry heuristic.

Real-world tests show improved coverage under forest canopy.

Abstract

Search and rescue missions are often critical following sudden natural disasters or in high-risk environmental situations. The most challenging search and rescue missions involve difficult-to-access terrains, such as dense forests with high occlusion. Deploying unmanned aerial vehicles for exploration can significantly enhance search effectiveness, facilitate access to challenging environments, and reduce search time. However, in dense forests, the effectiveness of unmanned aerial vehicles depends on their ability to capture clear views of the ground, necessitating a robust search strategy to optimize camera positioning and perspective. This work presents an optimized planning strategy and an efficient algorithm for the next best view problem in occluded environments. Two novel optimization heuristics, a geometry heuristic, and a visibility heuristic, are proposed to enhance search performance by selecting optimal camera viewpoints. Comparative evaluations in both simulated and real-world settings reveal that the visibility heuristic achieves greater performance, identifying over 90% of hidden objects in simulated forests and offering 10% better detection rates than the geometry heuristic. Additionally, real-world experiments demonstrate that the visibility heuristic provides better coverage under the canopy, highlighting its potential for improving search and rescue missions in occluded environments.