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UGV Path Optimization in UAV-Assisted Environments Using Visibility-Aware Path Simplification

delete2026-05-23
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OA
AI
M
Munasinghe, Isuru *
A
Asanka G. Perera *
S
Sreenatha Anavatti
M
Matt Garratt
DOI:10.3390/jsan15030041delete
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Abstract

Abstract

En 中文
This study proposes a modular path optimization framework for uncrewed ground vehicles (UGVs) in uncrewed aerial vehicle (UAV)-assisted navigation environments to improve the efficiency, smoothness, and executability of paths generated by classical grid-based path planning algorithms. The principal innovation of this work is the Visibility and Line-of-Sight Path Simplification (VLoSPS) algorithm, an algorithm-independent post-processing method that removes redundant waypoints through long-range axis-aligned visibility analysis while preserving path feasibility. VLoSPS is integrated with the Direction-Aware Path Planning Approach (DAPPA) to reduce angular deviations and improve directional continuity. The proposed framework is applicable to standard algorithms, including A*, Dijkstra, Breadth-First Search (BFS), and Depth-First Search (DFS), without modifying their internal search mechanisms. The main academic contributions comprise the formulation of a generalized post-processing architecture for UAV-derived occupancy maps, the introduction of a visibility-aware waypoint reduction strategy, and extensive validation using two synthetic maze datasets and three UAV-derived semantically segmented real-world datasets. On the Göttingen Maze Dataset, the VLoSPS and DAPPA pipeline reduced the average path lengths of A*, Dijkstra, BFS, and DFS by 5.42%, 9.46%, 10.44%, and 86.00%, respectively. The consistent improvements across real-world datasets demonstrate the effectiveness, computational feasibility, and general applicability of the proposed framework for UAV-assisted UGV path planning. The implementation code and benchmark resources developed in this study are publicly released to promote reproducibility and facilitate future research.
Keywords:
UAV-UGV collaboration
multi-robot systems
autonomous navigation
path planning
trajectory optimization
map-based navigation
search and rescue applications

Journal

Journal of Sensor and Actuator Networks cover
Journal of Sensor and Actuator Networks
IF:
4.2
Papers:
615
Citations:
1.6K

Organization

U
University of Moratuwa
Scholars:
186
Papers: 85
Citations: 0
U
university of new south wales
Scholars:
2.9K
Papers: 1.5K
Citations: 0
U
university of southern queensland
Scholars:
1.1K
Papers: 629
Citations: 2
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Cited Papers

Cited Papers

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Spline-Based RRT Path Planner for Non-Holonomic Robots
err2013-10-12
err84
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errYang, Kwangjin; Moon, Sangwoo; Yoo, Seunghoon; Kang, Jaehyeon; Doh, Nakju Lett; Kim, Hong Bong; Joo, Sanghyun
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UAVid: A semantic segmentation dataset for UAV imagery
err2020-07-01
err178
errOAAI
errLyu, Ye; Vosselman, George; Xia, Gui-Song; Yilmaz, Alper; Yang, Michael Ying
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