Swarm Communication, Localization and Navigation

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: closed (28 February 2023) | Viewed by 8214

Special Issue Editors


E-Mail Website
Guest Editor
Institute of Communications and Navigation Communications Systems, German Aerospace Center, 82234 Wessling, Germany
Interests: signal processing for wireless communications; swarm localization and navigation; estimation theory

E-Mail Website
Guest Editor
Institute of Communications and Navigation Communications Systems, German Aerospace Center, 82234 Wessling, Germany
Interests: wireless communications; signal processing; swarm localization and navigation; USRPs

Special Issue Information

Dear Colleagues,

Autonomous robotic swarms are an emerging concept envisioned for a variety of sensing applications in the field of space exploration, search and rescue, disaster management, and environmental monitoring. In a swarm system, a plethora of spatially separated autonomous agents regularly exchange information and coordinate to achieve a certain task in various environments, such as on the surface, in the air, in space or in the deep sea. Collaboration based on communication is key to increase the agent’s situational awareness and their navigation capability, which is essential for a high degree of autonomy. A robotic swarm requires, e.g.:

  1. High precision and real-time localization of agents and the objects of interest in their surroundings, especially in environments with no or limited GNSS availability;
  2. Joint system optimization and signal processing for communication, localization, sensing, timing, and control;
  3. Autonomous location/trajectory and multiobjective optimization of agents.

Despite the great potential of autonomous robotic swarms, navigation and joint system optimization is a challenging problem due to the high dimensionality of the network. Additionally, the interdisciplinary involvement of signal processing, communications, control, robotics, and artificial intelligence makes the design of a swarm system an exciting and timely relevant topic.

We strongly encourage interdisciplinary work, and topics of interest include but are not limited to:

  • Fundamentals on swarm/network navigation;
  • Cooperative localization, navigation, and SLAM;
  • Autonomous and swarm navigation;
  • Multiagent, multiobjective control and path planning;
  • Synchronization and age of information in swarm navigation;
  • Decentralized estimation and optimization;
  • Joint optimization for communication, localization, sensing, timing, and control;
  • Applying AI for swarm communication, localization, and navigation;
  • Swarm navigation techniques, testbeds, and experiments for specific applications such as autonomous vehicles, swarm robotics, space and deep-sea exploration, UAV networks, and WSNs.

Dr. Armin Dammann
Dr. Emanuel Staudinger
Guest Editors

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Keywords

  • Swarm
  • Localization
  • Communication
  • Navigation
  • Synchronization
  • Timing
  • Control
  • Exploration
  • SLAM

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Published Papers (4 papers)

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Research

20 pages, 9720 KiB  
Article
Limits on Cooperative Positioning for a Robotic Swarm with Time of Flight Ranging over Two-Ray Ground Reflection Channel
by Emanuel Staudinger, Robert Pöhlmann, Armin Dammann and Siwei Zhang
Electronics 2023, 12(9), 2139; https://doi.org/10.3390/electronics12092139 - 7 May 2023
Cited by 2 | Viewed by 1384
Abstract
Autonomous robotic swarms are envisioned for a variety of applications—for example, space exploration, search and rescue, and disaster management. Important features of a robotic swarm include its ability to share information within the network, to sense spatio-temporal processes such as gas distributions, and [...] Read more.
Autonomous robotic swarms are envisioned for a variety of applications—for example, space exploration, search and rescue, and disaster management. Important features of a robotic swarm include its ability to share information within the network, to sense spatio-temporal processes such as gas distributions, and to collaboratively enhance its navigation. In environments without infrastructure, the swarm elements can cooperatively estimate their position, e.g., based on the time of flight of exchanged radio signals. Cooperative positioning performance depends on the radio propagation environment. Free-space path loss is commonly used for performance assessment, which is an optimistic assumption. In this work, we investigate the limits to cooperative positioning and ranging based on the time of flight of radio signals over the more realistic two-ray ground reflection channel. We show that we obtain a ranging bias caused by the radio signal component reflected from the ground, and that the ranging error becomes bias-limited. In the positioning domain, we investigate how the ranging bias affects the cooperative positioning performance. As a result, we gain in cooperation, but the achievable positioning performance is significantly worsened by the ranging bias. As a conclusion, the two-ray ground reflection model should be considered to obtain realistic cooperative positioning limits. Full article
(This article belongs to the Special Issue Swarm Communication, Localization and Navigation)
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22 pages, 1562 KiB  
Article
Swarm Exploration and Communications: A First Step towards Mutually-Aware Integration by Probabilistic Learning
by Edgar Beck, Ban-Sok Shin, Shengdi Wang, Thomas Wiedemann, Dmitriy Shutin and Armin Dekorsy
Electronics 2023, 12(8), 1908; https://doi.org/10.3390/electronics12081908 - 18 Apr 2023
Cited by 1 | Viewed by 1565
Abstract
Swarm exploration by multi-agent systems relies on stable inter-agent communication. However, so far both exploration and communication have been mainly considered separately despite their strong inter-dependency in such systems. In this paper, we present the first steps towards a framework that unifies both [...] Read more.
Swarm exploration by multi-agent systems relies on stable inter-agent communication. However, so far both exploration and communication have been mainly considered separately despite their strong inter-dependency in such systems. In this paper, we present the first steps towards a framework that unifies both of these realms by a “tight” integration. We propose to make exploration “communication-aware” and communication “exploration-aware” by using tools of probabilistic learning and semantic communication, thus enabling the coordination of knowledge and action in multi-agent systems. We anticipate that by a “tight” integration of the communication chain, the exploration strategy will balance the inference objective of the swarm with exploration-tailored, i.e., semantic, inter-agent communication. Thus, by such a semantic communication design, communication efficiency in terms of latency, required data rate, energy, and complexity may be improved. With this in mind, the research proposed in this work addresses challenges in the development of future distributed sensing and data processing platforms—sensor networks or mobile robotic swarms consisting of multiple agents—that can collect, communicate, and process spatially distributed sensor data. Full article
(This article belongs to the Special Issue Swarm Communication, Localization and Navigation)
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17 pages, 718 KiB  
Article
A PDR/WiFi Indoor Navigation Algorithm Using the Federated Particle Filter
by Jian Chen, Shaojing Song and Zhihui Liu
Electronics 2022, 11(20), 3387; https://doi.org/10.3390/electronics11203387 - 19 Oct 2022
Cited by 17 | Viewed by 1998
Abstract
This paper offers a solution to challenge navigation in the indoor environment by making use of the existing infrastructure. Estimating pedestrian trajectory using pedestrian dead reckoning (PDR) and WiFi is a very popular technique. However, cumulative errors and mismatching are major problems in [...] Read more.
This paper offers a solution to challenge navigation in the indoor environment by making use of the existing infrastructure. Estimating pedestrian trajectory using pedestrian dead reckoning (PDR) and WiFi is a very popular technique. However, cumulative errors and mismatching are major problems in PDR and WiFi fingerprint matching, respectively. PDR and pedestrian heading are used as the state transition equation, and the step length and WiFi matching results are used as observation equations. A federated particle filter (FPF) based on the principle of information sharing is proposed to fusion PDR and WiFi, which improves pedestrian navigation accuracy. The experimental results show that the average positioning accuracy is 0.94 m and 1.5 m, respectively. Full article
(This article belongs to the Special Issue Swarm Communication, Localization and Navigation)
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15 pages, 1162 KiB  
Article
Distributed Event-Triggered Approach for Multi-Agent Formation Based on Cooperative Localization with Mixed Measurements
by Yanjun Lin, Zhiyun Lin and Zhiyong Sun
Electronics 2021, 10(18), 2265; https://doi.org/10.3390/electronics10182265 - 15 Sep 2021
Cited by 7 | Viewed by 2134
Abstract
This paper concentrates on multi-agent formation control problems under mixed measurements of distance and bearing. Towards this objective, a distributed event-triggered estimation-based control framework is developed such that only at necessary time instants, the event for estimation (namely, cooperative localization among a subgroup [...] Read more.
This paper concentrates on multi-agent formation control problems under mixed measurements of distance and bearing. Towards this objective, a distributed event-triggered estimation-based control framework is developed such that only at necessary time instants, the event for estimation (namely, cooperative localization among a subgroup of agents) is triggered to recover relative position information by utilizing a mixed distance and bearing measurements from different agents. Firstly, it is shown by using the stiffness theory that a subgroup of agents are capable of recovering relative position information if a sufficient number of independent distance and range measurements are available. Secondly, a distributed event-triggered mechanism is presented for achieving an affine formation control, which can be implemented in an asynchronous manner and also ensures Zeno-free behavior. Simulation studies are provided to demonstrate the effective performance of the proposed approach. Full article
(This article belongs to the Special Issue Swarm Communication, Localization and Navigation)
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