Optimal formation control and collision avoidance in environment with multiple rectangle obstacles

Shi, Zhengqing; He, Junda; Wang, Tengli; Zhou, Chuan; Guo, Jian

doi:10.1016/j.jfranklin.2018.07.042

Cited by 11 publications

(5 citation statements)

References 31 publications

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“…The tracking problem is one of the most hot issues in cooperative control of UAV, and has gained much attention in recent years due to its wide applications in various fields such as drone control, search and rescue missions, environmental monitoring, precision agriculture, infrastructure inspection, entertainment and so on [1][2][3][4]. One important representation of the mathematical model of UAV is the multi-agent systems.…”

Section: Introductionmentioning

confidence: 99%

Multi-Group Tracking Control for MASs of UAV with a Novel Event-Triggered Scheme

Zhao

Shi

Tang

et al. 2023

Drones

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The flight control of UAVs can be implemented and theoretically analyzed using multi-agent systems (MASs), and tracking control is one of the important control technologies. This paper studies multi-group tracking control for multi-agent systems of UAV, in which the control scheme combines event-triggered technology and impulsive theory. The advantage of multi-group tracking control lies in its ability to realize multiple groups of tracking targets and make the UAV complete multiple groups of tasks. The tracking control makes use of a novel dynamic event-triggered control (DETC) proposed in this paper, in which it can better regulate and optimize the triggering frequency by adjusting the parameters. Furthermore, several forms of network interference that may affect the safety of UAV tracking control have also been resolved. Lastly, simulations are presented with numerical examples to showcase the efficacy of the proposed tracking control.

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Section: Introductionmentioning

confidence: 99%

Multi-Group Tracking Control for MASs of UAV with a Novel Event-Triggered Scheme

Zhao

Shi

Tang

et al. 2023

Drones

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“…In further consideration toward practical applications, entities, such as consensus control, use dynamic graphs defined by the communication radii of agents (7,8) and in environments with obstacles (9,10) . The main objective of these study on dynamic graph are to achieve cooperative behavior with agents only using information related to their neighbors.…”

Section: Introductionmentioning

confidence: 99%

Average Consensus Problem in Multi-Agent System in an Environment with Obstacles

Kimura

Okuyama

2023

IEEJ Journal IA

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Multi-agent systems (MASs) are composed of multiple autonomous agents, and the overall behavior of an MAS is determined by the local interactions between its agents. In recent years, research on MASs aimed at their application in real-world environments has garnered considerable interest. In particular, consensus control in environments with constrained communication range of agents and obstacles is being extensively investigated. In this study, the consensus problem of MASs is examined by considering the effects of obstacles. In particular, an obstacle avoidance algorithm is developed as a control method for real-world autonomous machines such as autonomous mobile robots. In conventional control methods, obstacles are provided as coordinate points; however, in this study, they are introduced as variously shaped polygons. Furthermore, the graph topology is dynamic, which enables more realistic situations. Finally, a simulation study is performed, and the effectiveness of the developed algorithm for applying to the MAS consensus problem is demonstrated.

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“…Huang et al (2018) used the velocity obstacle algorithm to monitor the risk of ship collisions. Shi et al (2018) applied the velocity obstacle algorithm to solve a multi-agent collision avoidance problem. The above studies found that the velocity obstacle algorithm can assess the collision risk of a ship and rapidly find a collision-free solution in multiple-obstacle scenes.…”

Section: Introductionmentioning

confidence: 99%

Distributed Multi-Objective Algorithm for Preventing Multi-Ship Collisions at Sea

Wang

Guan

et al. 2020

J. Navigation

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Avoidance of collisions at sea is crucial to navigational safety. In this paper, we use a distributed algorithm to communicate the entire collision avoidance trajectory information for each ship. In each communication, we suggest a new improvement function considering safety and efficiency to identify the avoidance ship in each cycle. Considering the nonlinear collision avoidance trajectory of ships, a new method for calculating the degree of danger using a velocity obstacle algorithm is proposed. Therefore, in each communication, each ship considers the avoidance behaviours of other ships in planning its avoidance trajectory. Additionally, we combine bi-criterion evolution (BCE) and the ant lion optimiser to plan the entire collision avoidance path. Three scenarios are designed to demonstrate the performance of this method. The results show that the proposed method can find a suitable collision-free solution for all ships.

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Optimal formation control and collision avoidance in environment with multiple rectangle obstacles

Cited by 11 publications

References 31 publications

Multi-Group Tracking Control for MASs of UAV with a Novel Event-Triggered Scheme

Multi-Group Tracking Control for MASs of UAV with a Novel Event-Triggered Scheme

Average Consensus Problem in Multi-Agent System in an Environment with Obstacles

Distributed Multi-Objective Algorithm for Preventing Multi-Ship Collisions at Sea

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