Complexity in UAV cooperative control

Chandler, Phillip; Pachter, Meir; Darbha, Swaroop; Fowler, Jeffrey M.; Howlett, Josh; Rasmussen, Steven J.; Schumacher, Corey; Nygard, Kendall E.

doi:10.1109/acc.2002.1023833

Cited by 128 publications

(46 citation statements)

References 5 publications

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“…Rather, it may be necessary to coordinate several specialized units to attain complex objectives in a reliable, timely, and efficient fashion [1]. While considerable progress has been made on cooperative control of networks of homogeneous vehicles (see for example [2], [3], [4], [5]), heterogeneous networks are still relatively poorly understood. In such a direction recent developments aiming at spreading the adoption of unmanned systems in realworld operational scenarios- [6], [7]-consider the employment of cooperating mobile robots [8], often denoted as multiple mobile robot systems, combining the characteristics of heterogeneous vehicles with complementary features.…”

Section: Introductionmentioning

confidence: 99%

Cooperative mission planning for a class of carrier-vehicle systems

Garone

Naldi

Casavola

2010

49th IEEE Conference on Decision and Control (CDC)

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Abstract-In this work we focus on mission planning problems in scenarios in which a carrier vehicle, typically slow but with virtually infinite range, and a carried vehicle, which on the contrary is typically fast but has a shorter range, are coordinated to make the faster vehicle visit a given collection of points in minimum time. In particular in this paper we will address two mission planning problems: a first one, in which we have to sequentially visit a list of points under the hypothesis the takeoff/landing sequence is not determined a priori and a second one, a Traveling Salesman Problem (TSP), in which the optimal visiting sequence of points has to be determined. Those two problems will be analyzed, sub-optimal heuristics will be presented and their properties pointed out. I. INTRODUCTIONThe complexity of many applications envisioned for future autonomous vehicle networks, ranging from planetary exploration to rescue missions, requires a broad range of capabilities for individual units-ranging from air, ground or sea mobility, to sophisticated multi-modal sensor suites and actuation devices-which cannot be implemented on a single platform class. Rather, it may be necessary to coordinate several specialized units to attain complex objectives in a reliable, timely, and efficient fashion To understand how to optimally exploit the different capabilities of each individual unit and obtain the desired final behavior, the team is required to be suitably coordinated through advanced planning and control algorithms. In this paper, we concentrate on a very simple system of heterogeneous vehicles, arising from the combination of (i) a slow autonomous surface carrier (typically a ship) with long operating range capabilities and (ii) a faster vehicle (typically a helicopter, a UAV, or an offshore vehicle) with a limited range. The carrier is able to transport the faster vehicle, as well as to deploy, recover, and service it. Even though this two-vehicle system is very simple, it reveals new aspects of many path

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Section: Introductionmentioning

confidence: 99%

Cooperative mission planning for a class of carrier-vehicle systems

Garone

Naldi

Casavola

2010

49th IEEE Conference on Decision and Control (CDC)

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“…UAV assignment and task allocation problems, among the most studied topics, decompose the optimization of air-to-ground operations into several parts and study how to allocate and schedule the UAVs to perform tasks so as to maximize effectiveness of the overall mission., involving different geographical locations, goal assignment, trajectory optimization, and time or task requirements., The complexity and computation cost are dramatically increase with the increase of problem size [139,140]. 'Multi-tasking Multi-assignment problem' consists of two aspects: modeling and solving task assignment problem [141].…”

Section: Introductionmentioning

confidence: 99%

RhoGTPase Involvement in Breast Cancer Migration and Invasion

Simpson¹

2008

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“…The proposed method is also efficient in the sense that the synthesis procedure is based only on a single agent model, instead of a model of the whole formation with a possibly large number of agents. Graph theory has been used by Murray and Olfati-Saber [46] and Phillip R. Chandler [47] to control cooperating units. A control design based on decentralized Receding Horizon Control (RHC) was proposed [41] for collision-free UAV formation flight.…”

Section: Control Techniquesmentioning

confidence: 99%