Symmetry/Asymmetry in Control Science

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: closed (31 May 2024) | Viewed by 2028

Special Issue Editors

Qingdao Innovation and Development Center, Harbin Engineering University, Qingdao 266400, China
Interests: maps; navigation; 3D reconstruction; 3D modeling; IndoorGML; mobility as a service; space

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Guest Editor
Department of Automatic Control and Systems Engineering, The University of Sheffield, Sheffield S10 2TN, UK
Interests: machine learning; computational intelligence; statistical signal processing; robot SLAM; navigation and autonomous systems
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Special Issue Information

Dear Colleagues,

We are pleased to announce the upcoming Special Issue on "Symmetry/Asymmetry in Control Science". This Issue aims to explore how symmetry and asymmetry influence control science in the domain of robotics, such as Unmanned Aerial Vehicles (UAVs), Unmanned Ground Vehicles (UGVs), Unmanned Surface Vessels (USVs), Autonomous Surface Vehicles (ASVs), Unmanned Underwater Vehicles (UUVs), Space Exploration Vehicles (SEVs), Lunar Roving Vehicles, and Mars rovers. By reading this Special Issue, researchers and readers will gain insights into the development of novel control techniques, especially on how to enable more efficient, adaptable, and reliable robotic systems across domains such as aerial, ground, surface, underwater, space exploration, and lunar and planetary exploration. By addressing the challenges posed by asymmetries and harnessing the benefits of symmetries, we can unlock new possibilities and advancements in navigation, path planning, control, guidance, Simultaneous Localization and Mapping (SLAM), and other control techniques.

In the past decades, the field of robotics has witnessed remarkable advancements, enabling the deployment of various unmanned vehicles in diverse environments. Robotic systems are designed to operate autonomously in complex and challenging environments for a wide range of applications, from aerial surveillance and package delivery to ground-based exploration, underwater research, and extraterrestrial missions. The control science behind these robotic systems is crucial for achieving efficient and reliable operation in these demanding scenarios. Relevant topics include path planning, control, guidance, and SLAM.

Understanding the dynamics of symmetry and asymmetry is extremely important for developing efficient and robust control strategies because (i) symmetry analysis provides valuable insights into the structure and behaviour of robotic systems. By identifying and leveraging inherent symmetries, control strategies can be designed to exploit system properties, optimize navigation, enhance path planning, improve control, enable accurate guidance, and enable robust SLAM algorithms. Symmetry-based approaches have demonstrated significant success in various robotic applications, leading to improved performance, energy efficiency, and overall system reliability. (ii) Real-world scenarios often introduce asymmetries that impact the control and operation of robotic vehicles. Uneven terrains, varying water currents, sensor limitations, communication constraints, and the unpredictable nature of space exploration pose challenges that require innovative control solutions. Effectively addressing and adapting to these asymmetries is crucial for maintaining stability, safety, and mission success.

We kindly invite all researchers working in the area to contribute to this Special Issue.

Dr. Jinjin Yan
Dr. Lyudmila Mihaylova
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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

  • control science/strategies
  • robotics
  • Unmanned Aerial Vehicles (UAVs)
  • Unmanned Ground Vehicles (UGVs)
  • Unmanned Surface Vehicles (USVs)
  • Unmanned Underwater Vehicles (UUVs)
  • Space Exploration Vehicles (SEVs)
  • lunar roving vehicles
  • Mars rovers
  • navigation
  • path planning
  • Simultaneous Localization and Mapping (SLAM)

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Published Papers (1 paper)

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Research

20 pages, 10233 KiB  
Article
Global Multi-Scale Optimization and Prediction Head Attentional Siamese Network for Aerial Tracking
by Qiqi Chen, Jinghong Liu, Xuan Wang, Yujia Zuo and Chenglong Liu
Symmetry 2023, 15(9), 1629; https://doi.org/10.3390/sym15091629 - 24 Aug 2023
Cited by 2 | Viewed by 1040
Abstract
Siamese-based trackers have been widely used in object tracking. However, aerial remote tracking suffers from various challenges such as scale variation, viewpoint change, background clutter and occlusion, while most existing Siamese trackers are limited to single-scale and local features, making it difficult to [...] Read more.
Siamese-based trackers have been widely used in object tracking. However, aerial remote tracking suffers from various challenges such as scale variation, viewpoint change, background clutter and occlusion, while most existing Siamese trackers are limited to single-scale and local features, making it difficult to achieve accurate aerial tracking. We propose the global multi-scale optimization and prediction head attentional Siamese network to solve this problem and improve aerial tracking performance. Firstly, a transformer-based multi-scale and global feature encoder (TMGFE) is proposed to obtain global multi-scale optimization of features. Then, the prediction head attentional module (PHAM) is proposed to add context information to the prediction head by adaptively adjusting the spatial position and channel contribution of the response map. Benefiting from these two components, the proposed tracker solves these challenges of aerial remote sensing tracking to some extent and improves tracking performance. Additionally, we conduct ablation experiments on aerial tracking benchmarks, including UAV123, UAV20L, UAV123@10fps and DTB70, to verify the effectiveness of the proposed network. The comparisons of our tracker with several state-of-the-art (SOTA) trackers are also conducted on four benchmarks to verify its superior performance. It runs at 40.8 fps on the GPU RTX3060ti. Full article
(This article belongs to the Special Issue Symmetry/Asymmetry in Control Science)
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