Formation control of unmanned aerial vehicle swarms: A comprehensive review

Ouyang, Quan; Wu, Zhaoxiang; Cong, Yuhua; Wang, Zhisheng

doi:10.1002/asjc.2806

Cited by 30 publications

(3 citation statements)

References 129 publications

(142 reference statements)

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“…There are several attempts to produce a review on path planning techniques designed for multi-robot systems. However, the reviews published recently in the literature were limited to either reviewing only a specific robot type such as UAV-based systems [12], and UGV-based systems [13], or neglecting the formation control system which is an essential factor for multi-robot systems [13][14][15]. To the best of the author's knowledge, the literature lacks the presence of a recent study on the state-of-the-art path planning techniques designed for multi-robot formation systems.…”

Section: Introductionmentioning

confidence: 99%

A comprehensive review of the latest path planning developments for multi-robot formation systems

et al. 2023

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There has been a continuous interest in multi-robot formation systems in the last few years due to several significant advantages such as robustness, scalability, and efficiency. However, multi-robot formation systems suffer from well-known problems such as energy consumption, processing speed, and security. Therefore, developers are continuously researching for optimal solutions that can gather the benefits of multi-robot formation systems while overcoming the possible challenges. A backbone process required by any multi-robot system is path planning. Thus, path planning for multi-robot systems is a recent top research topic. However, the literature lacks a recent comprehensive review of path planning works designed for multi-robot systems. The aim of this review paper is to provide a comprehensive assessment and an insightful look into various path planning techniques developed in multi-robot formation systems, in addition to highlighting the basic problems involved in this field. This will allow the reader to discover the research gaps that must be solved for a better path planning experience for multi-robot formation systems. Finally, an illustrative comparative example is presented at the end of the paper to show the advantages and disadvantages of some popular path planning techniques.

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Section: Introductionmentioning

confidence: 99%

A comprehensive review of the latest path planning developments for multi-robot formation systems

et al. 2023

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“…With the objective to form and maintain a desired geometric structure on their states or outputs, distributed formation control has attracted much attention in the research communities of coordinated control for DMASs. In military and civil fields, distributed formation control was widely developed and applied, such as unmanned aerial vehicle formation [19], satellite network [20], multi‐robot cooperation [21], and multi‐missile cooperative attack [20]. Comparing the consensus control with the formation control, the consensus control protocol only relies on the local neighboring information, but the formation control protocol has an additional formation function.…”

Section: Introductionmentioning

confidence: 99%

Minimum‐energy time‐varying formation of distributed multi‐agent systems with interaction constraints

Qin

Wang

et al. 2023

Asian Journal of Control

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In the current paper, minimum‐energy time‐varying formation design and analysis problems of distributed multi‐agent systems (DMASs) subjected to randomly switching topologies and aperiodic interaction pauses are investigated, which can ensure the time‐varying formation achievement with the minimum‐energy consumption in the sense of the linear matrix inequality. Firstly, a formation control protocol is designed with local information of neighboring agents, where the total energy consumption during the formation process is constructed and the impacts of interaction constraints are imposed. Then, minimum‐energy formation design and analysis criteria of DMASs are presented in terms of the linear matrix inequality tool, which can be checked by the generalized eigenvalue method. Finally, a numerical simulation is shown to verify the effectiveness of the main results.

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“…It should be noted that the practical systems have multiple players [9], such as the large-scale industrial pro-cesses [10], the wireless network agents [11], the electrical power engineering [12], and the multiagent formation control [13,14]. Then, the integration of game theory with RL has led to extensive research in the field of multiplayer games [15,16].…”

Section: Introductionmentioning

confidence: 99%

Fully cooperative games with state and input constraints using reinforcement learning based on control barrier functions

Liu,

2023

Asian Journal of Control

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This paper provides a novel safe reinforcement learning (RL) control algorithm to solve safe optimal problems for fully cooperative (FC) games of discrete‐time multiplayer nonlinear systems with state and input constraints. The FC game is a special case of nonzero‐sum (NZS) games, where all players cooperate to accomplish a common task. The algorithm is proposed based on the policy iteration (PI) framework utilizing only the measured data along the system trajectories in the environment. Different from most works about PI, an effective method of obtaining initial safe and stable control policies is given here. In addition, control barrier functions (CBFs) and an input constraint function are introduced to augment reward functions. And the monotonically nonincreasing property of the iterative value function in the PI algorithm maintains the safe set forward invariant. Then, the neural networks are employed to approximate the system dynamics, the iterative control policies, and the iterative value function, respectively. Furthermore, the proposed algorithm is supported by theoretical proofs that guarantee both safety and convergence. Finally, the effectiveness and safety of the algorithm are illustrated by the results of the simulation.

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Formation control of unmanned aerial vehicle swarms: A comprehensive review

Cited by 30 publications

References 129 publications

A comprehensive review of the latest path planning developments for multi-robot formation systems

A comprehensive review of the latest path planning developments for multi-robot formation systems

Minimum‐energy time‐varying formation of distributed multi‐agent systems with interaction constraints

Fully cooperative games with state and input constraints using reinforcement learning based on control barrier functions

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