Smooth path planning based on geometric properties of no-fly zone

Fixed-wing unmanned aerial vehicles (UAVs) are frequently confronted with no-fly zones during mission execution, expecting the path planning to be performed under airspace constraints to meet designated requirement. In this study, a smooth path planning method based on the geometric properties of no-fly zones is proposed. It formulates the UAV flight path as a smooth combination of line segments and circular arcs, and models no-fly zones as circular or polygonal regions. By excavating the unique geometric properties of no-fly zones, intersections between the planned path and the no-fly zones can be efficiently detected, thereby reducing computational complexity and improving the accuracy of the generated path. This approach mitigates excessive conservativeness and significantly decreases the number of branches conditional checks. The resulting optimization problem is formulated as a nonlinear programming and solved using the Sequential Quadratic Programming (SQP) method. To evaluate the performance, simulations are conducted on both a desktop computer and an embedded demo board, followed by real-world validation on an unmanned platform. Experimental results demonstrate that the proposed algorithm exhibits remarkable adaptability and high execution efficiency.

Authors

Institutions

Publication Details

Journal
Transactions of the Institute of Measurement and Control
Published
2026-03-21
DOI
https://doi.org/10.1177/01423312261428511
Primary Topic
Robotic Path Planning Algorithms
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Smooth path planning based on geometric properties of no-fly zone

Ying Shi, Mingyu Sun, Jiahao Ma, Zengqiang Chen
Transactions of the Institute of Measurement and Control
Robotic Path Planning Algorithms
article

Smooth path planning based on geometric properties of no-fly zone

Ying Shi, Mingyu Sun, Jiahao Ma, Zengqiang Chen
article en

Abstract

Fixed-wing unmanned aerial vehicles (UAVs) are frequently confronted with no-fly zones during mission execution, expecting the path planning to be performed under airspace constraints to meet designated requirement. In this study, a smooth path planning method based on the geometric properties of no-fly zones is proposed. It formulates the UAV flight path as a smooth combination of line segments and circular arcs, and models no-fly zones as circular or polygonal regions. By excavating the unique geometric properties of no-fly zones, intersections between the planned path and the no-fly zones can be efficiently detected, thereby reducing computational complexity and improving the accuracy of the generated path. This approach mitigates excessive conservativeness and significantly decreases the number of branches conditional checks. The resulting optimization problem is formulated as a nonlinear programming and solved using the Sequential Quadratic Programming (SQP) method. To evaluate the performance, simulations are conducted on both a desktop computer and an embedded demo board, followed by real-world validation on an unmanned platform. Experimental results demonstrate that the proposed algorithm exhibits remarkable adaptability and high execution efficiency.

Transactions of the Institute of Measurement and Control
Nankai University (CN)
Sustainable cities and communities
Openalex Percentile: Top 13%
Robotic Path Planning Algorithms
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.