Decentralized Task Assignment for Unmanned Aerial Vehicles

Alighanbari, Mehdi; How, Jonathan P.

doi:10.1109/cdc.2005.1583066

Cited by 104 publications

(68 citation statements)

References 5 publications

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“…Our approach here is mainly centralized, however all but the combinatorial part of the solution can also be implemented in a decentralized way. As of this moment, we can not find an efficient way to solve the linear assignment problem without imposing significant computational and communication overhead [1].…”

Section: Organization and Overviewmentioning

confidence: 99%

Switched UAV-UGV Cooperation Scheme for Target Detection

Tanner

2007

Proceedings 2007 IEEE International Conference on Robotics and Automation

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Abstract-We develop a switched cooperative control scheme, to coordinate groups of ground and aerial vehicles for the purpose of locating a moving target in a given area. We do so by stabilizing the ground group into a guarding formation using a navigation function, and then steering the aerial group along a trajectory that uniformly scans the enclosed regions. The novelty of the approach lays in combining decentralized flocking algorithms with navigation functions for obstacle avoidance, convergence to designated position, and direction control.

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Section: Organization and Overviewmentioning

confidence: 99%

Switched UAV-UGV Cooperation Scheme for Target Detection

Tanner

2007

Proceedings 2007 IEEE International Conference on Robotics and Automation

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“…Finally, this paper also extends the results in Ref. [9] to consider the algorithm performance with different network topologies, with a particular focus on how best to allocate the communication resources between the different parts of the algorithm (information consensus and planning consensus).…”

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confidence: 97%

“…[9] demonstrated the benefit of adding the second communication phase, it also showed that the set of candidate plans chosen to be communicated can have a significant effect on the overall performance. The second stage of planning is based on this set of candidate plans and, because this is consistent between all UAVs, the final plan is guaranteed to have no conflicts.…”

mentioning

confidence: 99%

“…[9] and presented new insights on the issue of identifying the relative significance of various types of information that could be communicated. That paper also presented a new approach (called Robust Decentralized Task Assignment (RDTA)) to avoid conflicts in the decentralized planning wherein the UAVs communicate a set of candidate plans and plan independently using that information.…”

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confidence: 99%

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Robust Decentralized Task Assignment for Cooperative UAVs

Alighanbari

How

2006

AIAA Guidance, Navigation, and Control Conference and Exhibit

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This paper investigates the problem of decentralized task assignment for a fleet of cooperative UAVs. It extends the analysis of a previously proposed algorithm to consider the performance with different communication network topologies. The results show that the second communication step introduced during the planning phase of the new algorithm is crucial for sparse networks because the convergence rate of the information consensus algorithms can be quite slow. Further analysis shows that the selection of the candidate plans communicated during this planning phase has a significant impact on the performance of the overall algorithm. A comparison of the performance and computation of four selection approaches clearly shows the importance of correctly accounting for the potential actions of the other UAVs, even though that tends to be more computationally expensive. A modification of the original candidate plan selection algorithm is also presented, which further improves the overall performance by increasing the robustness to inconsistencies in the information across the team.

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“…An example is the problem involving time-discounted values of targets, 4,10,25 in which the sooner an agent arrives at the target, the higher the reward it obtains. A more complex mission scenario involves re-visit tasks, where previously observed targets must be revisited at some scheduled time.…”

Section: Iia Problem Statementmentioning

confidence: 99%

Asynchronous Decentralized Task Allocation for Dynamic Environments

Johnson

Ponda

Choi

et al. 2011

Infotech@Aerospace 2011

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This work builds on a decentralized task allocation algorithm for networked agents communicating through an asynchronous channel. The algorithm extends the Asynchronous Consensus-Based Bundle Algorithm (ACBBA) to account for more real time implementation issues resulting from a decentralized planner. This work utilizes a new implementation that allows further insight into the consensus and message passing structures of ACBBA. This paper specifically talks to the comparisons between global and local convergence in asynchronous consensus algorithms. Also a feature called asychronous replan is introduced to ACBBA's functionality that enables efficient updates to large changes in local situational awareness. A real-time software implementation using multiple agents communicating through the user datagram protocol (UDP) validates the proposed algorithm.

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Decentralized Task Assignment for Unmanned Aerial Vehicles

Cited by 104 publications

References 5 publications

Switched UAV-UGV Cooperation Scheme for Target Detection

Switched UAV-UGV Cooperation Scheme for Target Detection

Robust Decentralized Task Assignment for Cooperative UAVs

Asynchronous Decentralized Task Allocation for Dynamic Environments

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