Colored Multi-Agent Path Finding: Solving Approaches

Barták, Roman; Ivanová, Marika; Švancara, Jiří

doi:10.32473/flairs.v34i1.128535

Cited by 7 publications

(6 citation statements)

References 11 publications

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“…The approaches considered have limited success due to the weaknesses of the classifiers to adversarial learning attacks, as demonstrated by Shamir et al [34] and Eykholt et al [35]. On the intention determination front, drone maneuvers recognition has also been investigated, such as the work of Bartak and Vemlelova using Reinforcement Learning (RL) [36]. Using telemetry data, a Supervised Learning (SL) model to predict the formation of a drone swarm aims has been proposed by Traboulsi and Barbeau [37].…”

Section: Approach and Methodologymentioning

confidence: 99%

Research Trends in Collaborative Drones

Barbeau

García-Alfaro

Kranakis

2022

Sensors

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The last decade has seen an explosion of interest in drones—introducing new networking technologies, such as 5G wireless connectivity and cloud computing. The resulting advancements in communication capabilities are already expanding the ubiquitous role of drones as primary solution enablers, from search and rescue missions to information gathering and parcel delivery. Their numerous applications encompass all aspects of everyday life. Our focus is on networked and collaborative drones. The available research literature on this topic is vast. No single survey article could do justice to all critical issues. Our goal in this article is not to cover everything and include everybody but rather to offer a personal perspective on a few selected research topics that might lead to fruitful future investigations that could play an essential role in developing drone technologies. The topics we address include distributed computing with drones for the management of anonymity, countering threats posed by drones, target recognition, navigation under uncertainty, risk avoidance, and cellular technologies. Our approach is selective. Every topic includes an explanation of the problem, a discussion of a potential research methodology, and ideas for future research.

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Section: Approach and Methodologymentioning

confidence: 99%

Research Trends in Collaborative Drones

Barbeau

García-Alfaro

Kranakis

2022

Sensors

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“…There are recent works that are similar to our work. Barták, Švancara, and Vlk (2018) solve traditional MAPF via a scheduling-based approach. Specifically, they use a layered graph to represent delays.…”

Section: Related Workmentioning

confidence: 99%

Introducing Delays in Multi Agent Path Finding

Kottinger,

Geft,

Almagor

et al. 2024

SOCS

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We consider a Multi-Agent Path Finding (MAPF) setting where agents have been assigned a plan, but during its execution some agents are delayed. Instead of replanning from scratch when such a delay occurs, we propose delay introduction, whereby we delay some additional agents so that the remainder of the plan can be executed safely. We show that finding the minimum number of additional delays is APX-hard. However, in practice we can find optimal delay-introductions using Conflict-Based Search for very large numbers of agents, and both planning time and the resulting length of the plan are comparable, and sometimes outperform the state-of-the-art heuristics for replanning.

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“…The detailed description of proposed models and wider empirical evaluation is available at the full version of the paper (Barták, Ivanová, and Švancara 2021).…”

Section: Empirical Evaluationmentioning

confidence: 99%

From Classical to Colored Multi-Agent Path Finding

Barták

Ivanová

Švancara

2021

SOCS

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Multi-Agent Path Finding (MAPF) deals with the problem of finding collision-free paths for a set of agents moving in a shared environment, while each agent has specified its own destination. Colored MAPF generalizes MAPF by defining groups of agents that share a set of destination locations. In the paper, we evaluate several approaches to optimally solve colored MAPF problem, namely, a method based on network flows, an extended version of conflict-based search, and two models using Boolean satisfiability. We also investigate methods for obtaining lower bounds on optimal solutions based on constraint and continuous relaxation techniques.

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Colored Multi-Agent Path Finding: Solving Approaches

Cited by 7 publications

References 11 publications

Research Trends in Collaborative Drones

Research Trends in Collaborative Drones

Introducing Delays in Multi Agent Path Finding

From Classical to Colored Multi-Agent Path Finding

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