One-to-One Coordination Algorithm for Decentralized Area Partition in Surveillance Missions with a Team of Aerial Robots

Acevedo, José Joaquín; Arrue, Begoña C.; Díaz-Báñez, José Miguel; Ventura, Inmaculada; Maza, Iván; Ollero, A.

doi:10.1007/s10846-013-9938-z

Cited by 45 publications

(41 citation statements)

References 15 publications

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“…As it will become clear later, the virtual time and its first time derivative play a crucial role in the time-coordination problem. In fact, since the desired path assigned to each vehicle is parameterized by , we say that if (15) then, at time , all the vehicles are coordinated. Moreover, as already discussed in Section II, if…”

Section: A Definition Of the Time-coordination Objectivementioning

confidence: 99%

“…In the first case, each vehicle is driven along its own predefined time-dependent trajectory, provided by a central unit (controller). In the latter, each UAV runs its own guidance, navigation, and control algorithms, and is thus able to autonomously react to the behavior of other vehicles and/or unforeseen events to safely reach a mutual goal [15]- [20]. In the context of small multirotor UAVs (often featuring CPUs with relatively small capabilities), a hybrid (mix of centralized and decentralized) control can be applied to significantly reduce the exchange of information between the central controller and the UAVs.…”

Section: Introductionmentioning

confidence: 99%

“…1, where the vehicles are required to follow two paths of different lengths, while coordinating along the axis. In this paper, we aim at providing a solution which-differently from other works in the literature [2], [3], [8], [15], [16]-tackles the problem of decentralized cooperative control with time-varying communication networks through a Lyapunov-based approach, thus providing rigorous performance bounds as a function of the quality-of-service of the communication network. Moreover, we address the problem of non-ideal tracking performance of the UAVs, by showing that the time-coordination guarantees are retained even when the UAV does not converge-but remains close-to the desired position.…”

Section: Introductionmentioning

confidence: 99%

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Cooperative Path Following of Multiple Multirotors Over Time-Varying Networks

Cichella

Kaminer

Dobrokhodov

et al. 2015

IEEE Trans. Automat. Sci. Eng.

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This paper addresses the problem of time-coordination of a team of cooperating multirotor unmanned aerial vehicles that exchange information over a supporting time-varying network. A distributed control law is developed to ensure that the vehicles meet the desired temporal assignments of the mission, while flying along predefined collision-free paths, even in the presence of faulty communication networks, temporary link losses, and switching topologies. In this paper, the coordination task is solved by reaching consensus on a suitably defined coordination state. Conditions are derived under which the coordination errors converge to a neighborhood of zero. Simulation and flight test results are presented to validate the theoretical findings.Note to Practitioners-This paper presents an approach which enables a fleet of multirotor UAVs to follow a set of desired trajectories and coordinate along them, thus satisfying specific spatial and temporal assignments. The proposed solution can be employed in applications in which multiple vehicles are tasked to execute cooperative, collision-free maneuvers, and accomplish a common goal in a safely manner. An example is sequential monitoring, in which the UAVs have to visit and monitor a set of points of interest, while maintaining a desired temporal separation between each other. In this paper, we also simulate a scenario in which the vehicles, positioned in a square room, are required to exchange position with each other. It is shown that the proposed control algorithm not only ensures that the UAVs arrive at the final destinations at the same time, but also guarantees safety, i.e., the vehicles avoid collision with each other at all times.

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Section: A Definition Of the Time-coordination Objectivementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Cooperative Path Following of Multiple Multirotors Over Time-Varying Networks

Cichella

Kaminer

Dobrokhodov

et al. 2015

IEEE Trans. Automat. Sci. Eng.

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“…In previous work, the authors have implemented and applied early versions of our synchronization algorithms for the coordination of aerial robots in some simple scenarios for area exploration and surveillance missions [6], [7]. In this paper, we expand and formally present the theoretical results and algorithms that guarantee the synchronization of the team and show how to use our approach in a fault-tolerant cooperative system.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, different algorithms have been proposed for frequency-based multi-robot navigation. For example, in [5], partitioning and cyclic patrolling strategies are proposed and compared, and, in [6], the technique called one-to-one coordination is used to solve the area covering problem with a team of heterogeneous ARs. This technique is characterized by the fact that each pair of ARs solves a coordination problem including only their own information and requires the synchronization of the team for information exchange.…”

Section: Introductionmentioning

confidence: 99%

The synchronization problem for information exchange between aerial robots under communication constraints

Díaz-Báñez

Caraballo

Lopez

et al. 2015

2015 IEEE International Conference on Robotics and Automation (ICRA)

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This paper addresses a synchronization problem that arises when a team of aerial robots (ARs) need to communicate while performing assigned tasks in a cooperative scenario. Each robot has a limited communication range and flies within a previously assigned closed path. When two robots are close enough, a communication link may be established allowing the robots to share information. The goal is to schedule the flights such that the entire system can be synchronized for maximum information exchange, that is, every pair of neighbors are on the feasible communication link at the same time. We propose an algorithm for scheduling a team of robots in this scenario and propose a robust framework where the synchronization of a large team of robots is assured. The approach allows us to design a fault-tolerant system that can be used for multiple tasks such as surveillance, area exploration, searching for targets in a hazardous environment, and assembly and structure construction, to name a few.

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Cooperative Search, Reconnaissance, Surveillance

Joaquín

Arrue

Ollero

2016

Encyclopedia of Aerospace Engineering

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Cooperative search, reconnaissance, or surveillance with multiple aerial robots or unmanned aerial systems (UAS) is a well‐known topic in the literature. This chapter focuses on the high‐level problem addressing the multi‐UAS coordination, the cooperative strategy, and the coverage path‐planning issues. Experimental results and a large set of related references support the provided approaches.

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One-to-One Coordination Algorithm for Decentralized Area Partition in Surveillance Missions with a Team of Aerial Robots

Cited by 45 publications

References 15 publications

Cooperative Path Following of Multiple Multirotors Over Time-Varying Networks

Cooperative Path Following of Multiple Multirotors Over Time-Varying Networks

The synchronization problem for information exchange between aerial robots under communication constraints

Cooperative Search, Reconnaissance, Surveillance

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