Cooperative Relative Localization for UAV Swarm in GNSS-Denied Environment: A Coalition Formation Game Approach

Ruan, Lang; Li, Guangxia; Dai, Weiheng; Tian, Shengfeng; Gao, Fan; Jian, Wang; Dai, Xiaoqi

doi:10.1109/jiot.2021.3130000

Cited by 41 publications

(20 citation statements)

References 45 publications

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“…Theoretical analysis can refer to Section III (D) in [5]. Note that O-EDM rate has performance upper bound (100 %), the Algorithm 1: CG-based Tree-like Multistage Algo Input : Θ, Π, M, j = 1, maximal iteration time J. stable structure is generally the optimal solution of G. After coalition formation, coalitions need to determine their stages, so as to ensure a lower cumulative localization errors.…”

Section: Problem Solution and Algorithm Designmentioning

confidence: 99%

“…1, the CGG G 2 is proven to be a local Nash network. Generally, pairwise stability exists, which indicates GS-based Local Coordinate System Construction [5] 8 else 9 that G 2 can achieve a stable state. That is, no CU can improve its O-EDM rate through adjusting strategy.…”

Section: Problem Solution and Algorithm Designmentioning

confidence: 99%

“…fully connected requirements, which requires angle information. In [5], we improved MDS-MAP (P) by presenting a CFGbased two-stage clustering scheme. However, all those clustering schemes cannot adapt well to different topologies of networks and sometimes fall into the dilemma of error accumulation.…”

Section: Introductionmentioning

confidence: 99%

“…The main differences of our work with others can be summarized as: 1) Different from hop-based clustering [1]- [4] , this paper performs clustering for swarm based on the O-EDM rate. 2) Compared with the previous CFG-based clustering scheme in [5], a tree-like multistage clustering scheme based on CGG is designed to learn the optimal clustering and is more robust for irregular network topologies. This paper adopt asymmetric double-sided two-way ranging (ADS-TWR) in the time-of-flight (TOF) localization.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Multistage Clustering-Based Localization for Remote UAV Swarm: A Coalitional Game Framework

Ruan

Cheng

et al. 2022

IEEE Commun. Lett.

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In the GNSS-denied localization scenario, only received signals and corresponding distance measurements are available. Based on that, in this paper, we construct a multistage clustering-based model for UAV swarm. We characterize the proposed model as a coalition formation game (CFG) and provide corresponding preference criteria for algorithm design. A treelike multistage clustering mechanism is adopted based on a coalitional graph game (CGG). Each cluster (local map) performs localization calculation and then merges through neighboring drones (NDs) stage by stage. The simulation results show that the proposed scheme can achieve better localization accuracy than the comparison algorithms and is more robust for irregular network topologies.

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Section: Problem Solution and Algorithm Designmentioning

confidence: 99%

Section: Problem Solution and Algorithm Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Multistage Clustering-Based Localization for Remote UAV Swarm: A Coalitional Game Framework

Ruan

Cheng

et al. 2022

IEEE Commun. Lett.

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“…Localization can be divided into GNSS-based positioning and relative localization according to whether absolute location information can be obtained [5,6]. Biological swarms rely on sun and scene perception for self-positioning.…”

mentioning

confidence: 99%

A Survey of Robot Swarms’ Relative Localization Method

Chen

Yin

Niu

2022

Sensors

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For robot swarm applications, accurate positioning is one of the most important requirements for avoiding collisions and keeping formations and cooperation between individuals. However, in some worst cases, the GNSS (Global Navigation Satellite System) signals are weak due to the crowd being in a swarm or blocked by a forest, mountains, and high buildings in the environment. Thus, relative localization is an indispensable way to provide position information for the swarm. In this paper, we review the status and development of relative localization. It is first assessed that relative localization to obtain spatio-temporal relationships between individuals is necessary to achieve the stable operation of the group. After analyzing typical relative localization systems and algorithms from the perspective of functionality and practicality, this paper concludes that the UWB-based (ultra wideband) system is suitable for the relative localization of robots in large-scale applications. Finally, after analyzing the current challenges in the field of fully distributed localization for robotic swarms, a complete mechanism encompassing the relative localization process and the relationship between local and global localization that can be a possible direction for future research is proposed.

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Traffic offloading for postdisaster rescue in UAV‐assisted networks: A coalition formation game approach

Qiu,

Huang,

et al. 2023

Concurrency and Computation

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SummaryIn postdisaster rescue scenario, unmanned aerial vehicles (UAVs) are effective tools to help ground users in disaster areas to transmit rescue‐critical data to the relief center in time due to their flexible mobilities and fast deployment. However, how UAVs choose disaster areas to take part in traffic offloading with limited bandwidth resources is challenging. This article investigates UAVs' access selection and disaster areas' bandwidth allocation scheme by jointly optimizing network throughput, bandwidth and UAVs' energy cost. The UAVs form coalitions to participate in traffic offloading cooperatively, where each UAV selects a disaster area independently. Specifically, the bandwidth resources are dynamically allocated to all disaster areas when a new coalition partition forms. The UAVs adjust their access choices for disaster areas when the bandwidth allocation changes. When no UAVs migrate to other disaster areas, the network achieves a stable state. The UAVs fly to the final selected disaster area and provide traffic offloading services. To resolve traffic offloading competitions yet enable cooperations among UAVs, we address the UAVs' access selection issue by coalition formation game. A gradient projection method is then proposed to allocate bandwidth resources which maximizes the benefit of the network. We demonstrate that the UAVs' access selection and disaster areas' bandwidth allocation algorithms are convergent. The simulation results demonstrate that our proposed cooperation order is better than the pareto and selfish orders, thereby increasing the benefit of the network.

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Cooperative Relative Localization for UAV Swarm in GNSS-Denied Environment: A Coalition Formation Game Approach

Cited by 41 publications

References 45 publications

Multistage Clustering-Based Localization for Remote UAV Swarm: A Coalitional Game Framework

Multistage Clustering-Based Localization for Remote UAV Swarm: A Coalitional Game Framework

A Survey of Robot Swarms’ Relative Localization Method

Traffic offloading for postdisaster rescue in UAV‐assisted networks: A coalition formation game approach

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