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Drones
Special Issues
Efficient UAS Trajectory and Path Planning
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Efficient UAS Trajectory and Path Planning

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

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 3778

Special Issue Editors

Dr. Yifeng Niu

E-Mail Website
Guest Editor
College of Intelligence Science and Technology, National University of Defense Technology, Changsha 410073, China
Interests: multi-machine collaborative perception and decision; autonomous control; environmental perception and cognition
Special Issues, Collections and Topics in MDPI journals
Dr. Shaoqing Zhang

E-Mail Website
Guest Editor
Shenyang Aircraft Design and Research Institute, Shenyang, China
Interests: avionics systems design; multi-aircraft cooperative combat design and algorithm research; EMC design of aircraft
Dr. Fubiao Zhang

E-Mail Website
Guest Editor
School of Aerospace Engineering, Beijing Institute of Technology, Beijing 100081, China
Interests: flight dynamics; nonlinear and adaptive flight control
Dr. Jinwen Hu

E-Mail Website
Guest Editor
Key Laboratory of Information Fusion Technology, Ministry of Education, School of Automation, Northwestern Polytechnical University, Xi’an 710072, China
Interests: unmanned systems; information fusion; distributed control; navigation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Unmanned Aircraft Systems (UASs) have become an area of intense research within the robotics and control community. The research topics have covered a wide range of applications from civil to military domains, such as logistics, mine detection, building and environment monitoring, intruder detection and attacking, etc. An indispensable and fundamental capability that defines an “autonomous” UAS is Trajectory and Path planning (TPP) in adversarial environments. The objective of such capability is to complete the given mission, normally to arrive at a desired state within a time limit, while minimizing some costs of the UAVs. Time efficiency and safety are the key performance indices evaluating the TPP capability.

TPP design is related to navigation, body dynamics, environmental threats and flight mission, which result in the complexity of TPP modeling and derivation. In recent years, swarms or networks of UASs are emerging as a disruptive technology of highly reconfigurable intelligent autonomous systems. The complexity of TPP scales up by considering the interfering behaviors of partners in a swarm when a collaborative mission is executed. This Special Issue aims to collect papers (original research articles and review papers) that provide insights into the latest achievements of theory and practice related to the efficient TPP for UASs.

This Special Issue welcomes manuscripts that link the following themes:

  • Target search and tracking in complex environments;
  • Navigation and exploration in GPS-denied environments;
  • Autonomous decision-making for game and cooperation;
  • Cooperative path planning and re-planning for homogeneous/nonhomogeneous UAS swarms;
  • Learning-based and bio-inspired TPP for complex tasks;
  • Distributed optimization and parallel decision-making;
  • Fault-tolerant and robust TPP in disturbed and uncertain environments;
  • System design and tests for resource-constrained embedded applications;
  • Event-driven control strategies for silent and camouflaged UASs

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

Dr. Yifeng Niu
Dr. Shaoqing Zhang
Dr. Fubiao Zhang
Dr. Jinwen Hu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

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-blind 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

  • UAV
  • trajectory planning
  • path planning
  • decision-making
  • flight safety
  • swarm
  • distributed control

Published Papers (2 papers)

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Research

18 pages, 4124 KiB  
Article
MoNA Bench: A Benchmark for Monocular Depth Estimation in Navigation of Autonomous Unmanned Aircraft System
by Yongzhou Pan, Binhong Liu, Zhen Liu, Hao Shen, Jianyu Xu, Wenxing Fu and Tao Yang
Drones 2024, 8(2), 66; https://doi.org/10.3390/drones8020066 - 16 Feb 2024
Viewed by 1173
Abstract
Efficient trajectory and path planning (TPP) is essential for unmanned aircraft systems (UASs) autonomy in challenging environments. Despite the scale ambiguity inherent in monocular vision, characteristics like compact size make a monocular camera ideal for micro-aerial vehicle (MAV)-based UASs. This work introduces a [...] Read more.
Efficient trajectory and path planning (TPP) is essential for unmanned aircraft systems (UASs) autonomy in challenging environments. Despite the scale ambiguity inherent in monocular vision, characteristics like compact size make a monocular camera ideal for micro-aerial vehicle (MAV)-based UASs. This work introduces a real-time MAV system using monocular depth estimation (MDE) with novel scale recovery module for autonomous navigation. We present MoNA Bench, a benchmark for Monocular depth estimation in Navigation of the Autonomous unmanned Aircraft system (MoNA), emphasizing its obstacle avoidance and safe target tracking capabilities. We highlight key attributes—estimation efficiency, depth map accuracy, and scale consistency—for efficient TPP through MDE. Full article
(This article belongs to the Special Issue Efficient UAS Trajectory and Path Planning)
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18 pages, 25072 KiB  
Article
A Low-Altitude Obstacle Avoidance Method for UAVs Based on Polyhedral Flight Corridor
by Zhaowei Ma, Zhongming Wang, Aitong Ma, Yunzhuo Liu and Yifeng Niu
Drones 2023, 7(9), 588; https://doi.org/10.3390/drones7090588 - 19 Sep 2023
Cited by 2 | Viewed by 1432
Abstract
UAVs flying in complex low-altitude environments often require real-time sensing to avoid environmental obstacles. In previous approaches, UAVs have usually carried out motion planning based on primitive navigation maps such as point clouds and raster maps to achieve autonomous obstacle avoidance. However, due [...] Read more.
UAVs flying in complex low-altitude environments often require real-time sensing to avoid environmental obstacles. In previous approaches, UAVs have usually carried out motion planning based on primitive navigation maps such as point clouds and raster maps to achieve autonomous obstacle avoidance. However, due to the huge amount of data in these raw navigation maps and the highly discrete map information, the efficiency of solving the UAV’s real-time trajectory optimization is low, making it difficult to meet the demand for efficient online motion planning. A flight corridor is a series of unobstructed continuous areas and has convex properties. The flight corridor can be used as a simple parametric representation to characterize the safe flight space in the environment, and used as the cost of the collision term in the trajectory back-end optimization for trajectory solving, which can improve the efficiency of real-time trajectory solving and ensure flight safety. Therefore, this paper focuses on the construction of safe flight corridors for UAVs and autonomous obstacle avoidance algorithms for UAVs based on safe flight corridors, based on a rotary-wing UAV platform, and proposes a polyhedral flight corridor construction algorithm and realizes autonomous obstacle avoidance for UAVs based on the constructed flight corridors. Full article
(This article belongs to the Special Issue Efficient UAS Trajectory and Path Planning)
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