Application of distributed auction to multi-UAV task assignment in agriculture

Hu, Jie; Yang, Jiacheng

doi:10.33440/j.ijpaa.20180101.0008

Cited by 14 publications

(14 citation statements)

References 14 publications

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“…Theorem 1. Consider a multi-UAV system with n vehicles whose motion are modelled as (10). Under Assumptions 2-5, the distributed control law (16) (or (17) for bounded inputs) along with the algorithm in S1-S4 solves the 3D barrier coverage problem defined in Problem 1.…”

Section: Assumption 4 the Voronoi Neighbours Of Pbmentioning

confidence: 99%

“…Theorem 2. Consider a multi-UAV system of size n where each vehicle's motion model is represented by (10). The control law (16) along with the algorithm in S1-S4 defined for a sweeping region F (t) whose dynamics is governed by (25) solves the 3D sweeping coverage problem defined in Problem 2 under Assumptions 2-6 and the condition (26).…”

Section: Sweep Coverage Control Designmentioning

confidence: 99%

“…Unmanned aerial vehicles (UAVs) have become a popular choice in this area to form MWSNs especially in places inaccessible by ground vehicles. In general, multi-UAV systems have been emerging in various applications such as precision agriculture [9][10][11][12][13], aerial manipulation and transportation [14][15][16][17][18], search and rescue [14,19,20], firefighting [21], surveillance and monitoring [22,23], mapping and exploration [24][25][26], etc.…”

Section: Introductionmentioning

confidence: 99%

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Computationally-Efficient Distributed Algorithms of Navigation of Teams of Autonomous UAVs for 3D Coverage and Flocking

Elmokadem

Savkin

2021

Drones

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This paper proposes novel distributed control methods to address coverage and flocking problems in three-dimensional (3D) environments using multiple unmanned aerial vehicles (UAVs). Two classes of coverage problems are considered in this work, namely barrier and sweep problems. Additionally, the approach is also applied to general 3D flocking problems for advanced swarm behavior. The proposed control strategies adopt a region-based control approach based on Voronoi partitions to ensure collision-free self-deployment and coordinated movement of all vehicles within a 3D region. It provides robustness for the multi-vehicle system against vehicles’ failure. It is also computationally-efficient to ensure scalability, and it handles obstacle avoidance on a higher level to avoid conflicts in control with the inter-vehicle collision avoidance objective. The problem formulation is rather general considering mobile robots navigating in 3D spaces, which makes the proposed approach applicable to different UAV types and autonomous underwater vehicles (AUVs). However, implementation details have also been shown considering quadrotor-type UAVs for an example application in precision agriculture. Validation of the proposed methods have been performed using several simulations considering different simulation platforms such as MATLAB and Gazebo. Software-in-the-loop simulations were carried out to asses the real-time computational performance of the methods showing the actual implementation with quadrotors using C++ and the Robot Operating System (ROS) framework. Good results were obtained validating the performance of the suggested methods for coverage and flocking scenarios in 3D using systems with different sizes up to 100 vehicles. Some scenarios considering obstacle avoidance and robustness against vehicles’ failure were also used.

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Section: Assumption 4 the Voronoi Neighbours Of Pbmentioning

confidence: 99%

Section: Sweep Coverage Control Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Computationally-Efficient Distributed Algorithms of Navigation of Teams of Autonomous UAVs for 3D Coverage and Flocking

Elmokadem

Savkin

2021

Drones

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“…For example, Kim et al [12] propose a resource-oriented, distributed auction algorithm, which considers multiple resources of the agents and limited communication range. In [25], it uses a distributed auction algorithm to handle the task assignment problem while taking path planning into account. Because of using a well constructive distributed auction algorithm, the method in literature [26] can provide desirable assignment results in the constraint of limited resources and deadlines.…”

Section: Introductionmentioning

confidence: 99%

A Novel Hybrid Auction Algorithm for Multi-UAVs Dynamic Task Assignment

et al. 2020

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The auction algorithm is a widely used method for task assignments. However, most existing auction algorithms yield poor performance when applied to multi-UAVs dynamic task assignment. To end this, we propose a novel hybrid ''Two-Stage'' auction algorithm based on the hierarchical decision mechanism and an improved objective function, which simultaneously realizes heterogeneous multi-UAVs dynamic task assignment with limited resources of each UAV and avoidance obstacle path planning. In the first stage, according to the novel proposed hierarchical decision mechanism, we select a task that is urgently needed to be performed in the task group by using the decision function and three attribute values of tasks. After the first stage, it will result in a reasonable auction sequence, instead of random auction sequence as in previous algorithms. In the second stage, by considering the coverage factor and adaptive-limitation penalty term, a novel objective function is proposed and directs related UAVs for auction. In addition, we combine the structural advantages of the centralized and distributed auction algorithm, which greatly promotes its performance in dynamic task assignment. The experimental results demonstrate that the proposed method outperforms many state-of-the-art models in efficiency and robustness. INDEX TERMS Hierarchical decision mechanism, unmanned air vehicle, dynamic task assignment, auction algorithm, decision function.

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“…When huge dimension fields have to be covered in an agricultural mission, using a fleet of vehicles can be a solution so as to reduce the total time required to complete the mission, and therefore, obtain more homogeneous images due to possible changes in light [21][22][23][24][25][26].…”

mentioning

confidence: 99%

Unmanned Aerial Vehicles in Agriculture: A Survey

et al. 2021

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The number of tasks that nowadays are accomplished by using unmanned aerial vehicles is rising across many civil applications, including agriculture. Thus, this work aims at providing the reader with an overview of the agronomical use of unmanned aerial vehicles. The work starts with a historical analysis of the use of aircrafts in agriculture, as pioneers of their use in modern precision agriculture techniques, currently applied by a high number of users. This survey has been carried out by providing a classification of the vehicles according to their typology and main sensorial and performance features. An extensive review of the most common applications and the advantages of using unmanned aerial vehicles is the core of the work. Finally, a brief summary of the key points of the legislation applicable to civil drones that could affect to agricultural applications is analyzed.

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Application of distributed auction to multi-UAV task assignment in agriculture

Cited by 14 publications

References 14 publications

Computationally-Efficient Distributed Algorithms of Navigation of Teams of Autonomous UAVs for 3D Coverage and Flocking

Computationally-Efficient Distributed Algorithms of Navigation of Teams of Autonomous UAVs for 3D Coverage and Flocking

A Novel Hybrid Auction Algorithm for Multi-UAVs Dynamic Task Assignment

Unmanned Aerial Vehicles in Agriculture: A Survey

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