A Genetic Mission Planner for Solving Temporal Multi-agent Problems with Concurrent Tasks

Miloradović, Branko; Çürüklü, Baran; Ekström, Mikael

doi:10.1007/978-3-319-61833-3_51

Cited by 12 publications

(10 citation statements)

References 6 publications

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“…The mission plan is generated at the MMT using one of the available high-level planners [46][47][48], and sent to the MTTR through an Apache Thrift [49,50] interface using an ad hoc format whose structure is shown in Figure 3.…”

Section: The Mission Planmentioning

confidence: 99%

“…Figure 2 illustrates the SWARMs ontology for mission and planning. The mission plan is generated at the MMT using one of the available high-level planners [47][48][49], and sent to the MTTR through an Apache Thrift [50,51] interface using an ad hoc format whose structure is shown in Figure 3. Each mission plan is identified by its missionId, and consists of a hierarchical list of actions and the list of vehicles participating in the mission.…”

Section: The Mission Planmentioning

confidence: 99%

See 1 more Smart Citation

Proposal of an Automated Mission Manager for Cooperative Autonomous Underwater Vehicles

Martínez¹,

Martínez-Ortega²,

Rodríguez‐Molina³

et al. 2020

Applied Sciences

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In recent years there has been an increasing interest in the use of autonomous underwater vehicles (AUVs) for ocean interventions. Typical operations imply the pre-loading of a pre-generated mission plan into the AUV before being launched. Once deployed, the AUV waits for a start command to begin the execution of the plan. An onboard mission manager is responsible for handling the events that may prevent the AUV from following the plan. This approach considers the management of the mission only at the vehicle level. However, the use of a mission-level manager in coordination with the onboard mission manager could improve the handling of exogenous events that cannot be handled fully at the vehicle level. Moreover, the use of vehicle virtualization by the mission-level manager can ease the use of older AUVs. In this paper, we propose a new mission-level manager to be run at a control station. The proposed mission manager, named Missions and Task Register and Reporter (MTRR), follows a decentralized hierarchical control pattern for self-adaptive systems, and provides a basic virtualization in regard to the AUV’s planning capabilities. The MTRR has been validated as part of the SWARMs European project. During the final trials we assessed its effectiveness and measured its performance. As a result, we have identified a strong correlation between the length of mission plan and the time required to start a mission ( ρ s = 0.79 , n = 45 , p 0.001 ). We have also identified a possible bottleneck when accessing the repositories for storing the information from the mission. Specifically, the average time for storing the received state vectors in the relational database represented only 18.50% of the average time required for doing so in the semantic repository.

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Section: The Mission Planmentioning

confidence: 99%

Section: The Mission Planmentioning

confidence: 99%

Proposal of an Automated Mission Manager for Cooperative Autonomous Underwater Vehicles

Martínez¹,

Martínez-Ortega²,

Rodríguez‐Molina³

et al. 2020

Applied Sciences

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“…Tasks that are considered atomic from a high-level planning perspective, can be seen as divisible at the low level perspective, e.g., when agents need to coordinate to complete a more complex task. For example, Miloradović et al [9] considered MR tasks as atomic in a high-level mission planning approach, while Zlot [13] deal with the task decomposition and allocation with Logical Operators (LO).…”

Section: Relationshipsmentioning

confidence: 99%

TAMER: Task Allocation in Multi-robot Systems Through an Entity-Relationship Model

Miloradović

Frasheri

Çürüklü

et al. 2019

PRIMA 2019: Principles and Practice of Multi-Agent Systems

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Multi-robot task allocation (MRTA) problems have been studied extensively in the past decades. As a result, several classifications have been proposed in the literature targeting different aspects of MRTA, with often a few commonalities between them. The goal of this paper is twofold. First, a comprehensive overview of early work on existing MRTA taxonomies is provided, focusing on their differences and similarities. Second, the MRTA problem is modelled using an Entity-Relationship (ER) conceptual formalism to provide a structured representation of the most relevant aspects, including the ones proposed within previous taxonomies. Such representation has the advantage of (i) representing MRTA problems in a systematic way, (ii) providing a formalism that can be easily transformed into a software infrastructure, and (iii) setting the baseline for the definition of knowledge bases, that can be used for automated reasoning in MRTA problems.

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“…EUROPtus ensures that the priority for goals is determined on the operator side, mitigating this issue. A genetic algorithm approach by Miloradović, Çürüklü, and Ekström () is designed to allocate and schedule abstract tasks for a fleet of heterogeneous AUVs, but has yet to be implemented on simulated or real robots.…”

Section: Cooperation or Collaboration: Nuances In Multirobot Systems mentioning

confidence: 99%

“…Multiagent planning for AMV fleets has been in the literature since Sotzing, Evans, and Lane (), where the agents represented individual AMVs. The previously mentioned genetic algorithm approach by Miloradović et al () represents a multiagent system of AUVs using PDDL for temporal domain planning. The key differences in multiagent planners are discussed further in Section .…”

Section: Cooperation or Collaboration: Nuances In Multirobot Systems mentioning

confidence: 99%

Review of mission planning for autonomous marine vehicle fleets

Thompson

Guihen

2018

Journal of Field Robotics

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The deployment of a fleet of autonomous marine vehicles (AMVs) allows for the parallelisation of missions, intervehicle support for longer deployment times, adaptability and redundancy to in situ mission changes, and effective use of the right vehicle for the right purpose. End users and operators of AMVs face challenges in planning complex missions due to the limitations of their vehicles, dynamic, operationally constrictive, and unstructured environments, and in minimising risks to equipment, the mission, and personnel. Automated mission planning for AMV fleets can be a tool to reduce the complexity of programming vehicle tasking, and to perform validity assessments for end user-specified goals, allowing the operator to focus on risk assessment. We present a critical review of the current advances in automated planning for AMV fleets, investigating the limitations of available state-ofthe-art tools and providing a road map of the goals and challenges based on analysis of field reports and end user initiatives.

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A Genetic Mission Planner for Solving Temporal Multi-agent Problems with Concurrent Tasks

Cited by 12 publications

References 6 publications

Proposal of an Automated Mission Manager for Cooperative Autonomous Underwater Vehicles

Proposal of an Automated Mission Manager for Cooperative Autonomous Underwater Vehicles

TAMER: Task Allocation in Multi-robot Systems Through an Entity-Relationship Model

Review of mission planning for autonomous marine vehicle fleets

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