Continuous Monitoring of a Path-Constrained Moving Target by Multiple Unmanned Aerial Vehicles

Tabasso, Camilla; Kielas-Jensen, Calvin; Cichella, Venanzio; Manyam, Satyanarayana G.; Casbeer, David W.; Weintraub, Isaac E.

doi:10.2514/1.g006043

Cited by 2 publications

(3 citation statements)

References 20 publications

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“…where k ϕ ≜ √ 2nk, the second inequality follows from (13), and the other inequalities follow from (14). The GUES of ( 17) can now be used to define a Lyapunov function candidate to analyze stability of (16) as presented in the subsequent discussion. Since the system (17) is GUES, Theorem 4.12 in [31] implies that there exists a continuously differentiable, symmetric, positive definite matrix Ψ(t) such that…”

Section: Resultsmentioning

confidence: 99%

“…This condition, connectedness in an integral sense, was used in [14], [15] to show that collision avoidance can be achieved as well as the time-coordination. In the work reported in [16] the researchers applied the time-coordination algorithm [13] to the problem of continuous monitoring of a path-constrained moving target. Our recent work [17] showed convergence of time-coordination algorithms for a more general connectivity condition: the communication network is no longer required to be bidirectional.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Time Coordination of Multiple UAVs over Switching Communication Networks with Digraph Topologies

Hyungsoo

Yoon

Cichella

et al. 2021

2021 60th IEEE Conference on Decision and Control (CDC)

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In this article, a novel time-coordination algorithm based on event-triggered communications is proposed to achieve coordinated path-following of UAVs. To be specific, in the approach adopted a UAV transmits its progression information over a time-varying network to its neighbors only when a decentralized trigger condition is satisfied, thereby significantly reducing the volume of inter-vehicle communications required when compared with the existing algorithms based on continuous communications. Using such intermittent communications, it is shown that a decentralized coordination controller guarantees exponential convergence of the coordination error to a neighborhood of zero. Also, a lower bound on the interval between two consecutive event-triggered times is provided showing that the chattering issue does not arise with the proposed algorithm. Finally, simulation results validate the efficacy of the proposed algorithm.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Time Coordination of Multiple UAVs over Switching Communication Networks with Digraph Topologies

Hyungsoo

Yoon

Cichella

et al. 2021

2021 60th IEEE Conference on Decision and Control (CDC)

View full text Add to dashboard Cite

show abstract

“…Moreover, the research and design activities of UVs are facing a major transformation in the past two decades [4], [5]. While previously the focus was on developing large vehicles capable of carrying significant payloads over large distances, the recent technological improvements have shifted research and industrial interests to cooperative and autonomous operations involving multiple UVs [6], forming full-fledged multi-UV systems and achieving common objectives that may be dynamically changed during the mission execution.…”

Section: Introductionmentioning

confidence: 99%

Learning-in-Games Approach for the Mission Planning of Autonomous Multi-Drone Spatio-Temporal Sensing

Castrillo,

Pascarella,

Pigliasco

et al. 2024

IEEE Access

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Mission planners are one of the major classes of autonomy software and their design is especially challenging in the case cooperation autonomy is required for unmanned multi-vehicle systems. A clear example of this is given by the applications of teams of drones, such as multi-drone spatio-temporal sensing. Here, drone teams act as mobile and cooperative sensor networks to simultaneously collect sensor data in areas of interest and to allow detailed computation on the sensed data. For the design of cooperative and autonomous drone teams, mission planning shall be accomplished in the form of coordinated sensing to optimally assign the different sensing tasks and routes to each drone, employing task allocation and route planning as the basic pillars to maximize the multi-drone mission effectiveness. This work proposes a dynamic and decentralized mission planner for a drone team performing autonomous and cooperative spatiotemporal sensing. The design exploits the learning-in-games framework for the processing of optimal routes in reasonable time frames. Two ad-hoc variants of the binary log-linear learning are proposed as a coordination algorithm to manage both task allocation and route planning, by demonstrating reachability and reversibility properties. Also, the work describes an experimental analysis of the proposed solutions by means of model-in-the-loop simulations, in order to provide a preliminary tune of the main learning parameters for both solutions.INDEX TERMS Multi-drone systems, multi-drone sensing, learning in games, multi-agent systems.

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Continuous Monitoring of a Path-Constrained Moving Target by Multiple Unmanned Aerial Vehicles

Cited by 2 publications

References 20 publications

Time Coordination of Multiple UAVs over Switching Communication Networks with Digraph Topologies

Time Coordination of Multiple UAVs over Switching Communication Networks with Digraph Topologies

Learning-in-Games Approach for the Mission Planning of Autonomous Multi-Drone Spatio-Temporal Sensing

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