Path Planning, Trajectory Tracking and Guidance for UAVs: 4th Edition

A special issue of Drones (ISSN 2504-446X).

Deadline for manuscript submissions: 18 February 2027 | Viewed by 424

Editors

Department of Precision Instruments, Tsinghua University, Beijing 100190, China
Interests: cooperative guidance; intelligent guidance; trajectory planning; aircraft control; sensor fusion; aircraft simulations; reinforcement learning
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Guest Editor
School of Aeronautics and Astronautics, Zhejiang University, Zhejiang 310058, China
Interests: guidance, navigation, and control; flight dy-namics and simulations; optimal control and optimization
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Guest Editor
1. Department of Precision Instrument, Tsinghua University, Beijing 100084, China
2. State Key Laboratory of Precision Space-Time Information Sensing Technology, Beijing 100084, China
Interests: aerodynamic modeling; aerodynamic design optimization; large language model; autonomous decision-making
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Path planning, trajectory tracking, and guidance are essential aspects for the autonomous operations of Unmanned Aerial Vehicles (UAVs). These processes involve the determination of the optimal path, implementation of the planned path, and real-time adjustments to ensure accurate tracking and obstacle avoidance. The ability to plan efficient and safe paths for UAVs is crucial for the successful completion of missions, especially in complex environments. Moreover, the implementation of planned paths while considering external factors such as wind and turbulence, along with real-time guidance adjustment, ensures UAV’s safety and stability. Research in this area focuses on developing advanced algorithms and control systems that enable UAVs to operate autonomously and effectively in complex environments.

This Special Issue aims to collect the latest research results for path planning, trajectory tracking, and guidance of UAVs, which are fundamentally important for the autonomous operations of UAVs.

Papers are solicited in areas directly related to topics including, but not limited to, the following:

  • Path planning and task assignment for UAV swarms (as well as ground and underwater robots);
  • Autonomous navigation and localization (both outdoor and indoor);
  • Autonomous decision making;
  • Trajectory planning and optimization;
  • Guidance for individual UAV or for multiple cooperative UAVs;
  • Control algorithms;
  • Data-driven guidance and control;
  • AI-based planning.
  • Large Language Models (LLMs) for autonomous reasoning, planning, and control.

We look forward to receiving your original research articles and reviews.

Dr. Heng Shi
Dr. Minchi Kuang
Prof. Dr. Zheng Chen
Dr. Chenzhou Xu
Prof. Dr. Jihong Zhu
Guest Editors

Manuscript Submission Information

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Drones is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • path planning
  • trajectory tracking
  • guidance, navigation, and control
  • autonomous control
  • trajectory optimization
  • formation and reconfiguration

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Published Papers (1 paper)

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Research

42 pages, 30084 KB  
Article
GeoSOT-H-Enabled Risk-Aware Hierarchical Path Planning and Emergency Replanning for Urban Low-Altitude UAV Missions
by Hongbin Liu, Liang Zeng, Mengyuan Lu, Ke Tang, Bo Li and Xinping Zhu
Drones 2026, 10(8), 603; https://doi.org/10.3390/drones10080603 - 5 Aug 2026
Viewed by 135
Abstract
Urban low-altitude UAV missions require efficient, risk-aware path planning and rapid response to dynamic airspace changes. This study proposes a hierarchical planning and dynamic replanning framework based on the Geographic coordinate Subdivision grid with One-dimensional integer coding on a 2n-Tree (GeoSOT) [...] Read more.
Urban low-altitude UAV missions require efficient, risk-aware path planning and rapid response to dynamic airspace changes. This study proposes a hierarchical planning and dynamic replanning framework based on the Geographic coordinate Subdivision grid with One-dimensional integer coding on a 2n-Tree (GeoSOT) and height-layer encoding (GeoSOT-H). The framework constructs a multi-granularity 3D semantic-risk voxel model and uses semantic-triggered refinement to limit fine-resolution modeling to flight-relevant high-risk regions. The Hierarchical Semantic-risk-aware Path Planning with Corridor-constrained A* (HSPC-A*) algorithm generates a macro-corridor and conducts fine-level search to balance path length, semantic-risk exposure, and vertical maneuvering cost while satisfying no-fly constraints. Its output is a connected L24-H voxel-center path for subsequent navigation or post-processing. Experiments in a 2.89 km2 urban area show that explicit storage is reduced to 16.4% of full-domain L24-H voxels. Compared with conventional 3D A*, HSPC-A* slightly increases path length from 2183.06 m to 2202.38 m, while reducing average semantic risk from 8.5927 to 5.2595, eliminating high-risk samples, and reducing search time from 164.09 s to 3.74 s. Code-based updating achieved a 104.6-fold speedup, and two-branch replanning handled both corridor-retained and corridor-disconnecting no-fly events, jointly demonstrating the trade-offs among path length, semantic-risk exposure, computational efficiency, and compliance with modeled flight-safety constraints. Full article
(This article belongs to the Special Issue Path Planning, Trajectory Tracking and Guidance for UAVs: 4th Edition)
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