pRoPhEt MAS: Reactive Planning Engine for Multiagent Systems

Saur, Daniel; Geihs, Kurt

doi:10.1007/978-3-319-08338-4_12

Cited by 2 publications

(3 citation statements)

References 6 publications

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“…Based on this information exchange, agents can infer and act upon the state of other agents. ALICA has more recently been extended (Saur and Geihs, 2015 ) to support integration with the pRoPhEt planning engine for MASs (Saur and Geihs, 2014 ).…”

Section: Other Workmentioning

confidence: 99%

Toward Formal Models and Languages for Verifiable Multi-Robot Systems

2018

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Incorrect operations of a Multi-Robot System (MRS) may not only lead to unsatisfactory results, but can also cause economic losses and threats to safety. These threats may not always be apparent, since they may arise as unforeseen consequences of the interactions between elements of the system. This call for tools and techniques that can help in providing guarantees about MRSs behaviour. We think that, whenever possible, these guarantees should be backed up by formal proofs to complement traditional approaches based on testing and simulation.We believe that tailored linguistic support to specify MRSs is a major step towards this goal. In particular, reducing the gap between typical features of an MRS and the level of abstraction of the linguistic primitives would simplify both the specification of these systems and the verification of their properties. In this work, we review different agent-oriented languages and their features; we then consider a selection of case studies of interest and implement them useing the surveyed languages. We also evaluate and compare effectiveness of the proposed solution, considering, in particular, easiness of expressing non-trivial behaviour.

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Section: Other Workmentioning

confidence: 99%

Toward Formal Models and Languages for Verifiable Multi-Robot Systems

2018

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“…The planning framework pRoPhEt MAS [4] is shown in Figure 18. World and ALICA Engine are the basic components of the framework.…”

Section: Planning Enginementioning

confidence: 99%

“…All skills of the robots are defined using our coordination language A Language for Interactive Agents (ALICA) [3]. The mission is guided by the planning system Reactive Planning Engine for Multi-Agent Systems (pRoPhEt MAS) [4]. The control center starts the mission interactively by defining the goal state using a logic description.…”

Section: Introductionmentioning

confidence: 99%

IMPERA: Integrated Mission Planning for Multi-Robot Systems

Saur

Geihs

2015

Robotics

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This paper presents the results of the project IMPERA (Integrated Mission Planning for Distributed Robot Systems). The goal of IMPERA was to realize an extraterrestrial exploration scenario using a heterogeneous multi-robot system. The main challenge was the development of a multi-robot planning and plan execution architecture. The robot team consists of three heterogeneous robots, which have to explore an unknown environment and collect lunar drill samples. The team activities are described using the language ALICA (A Language for Interactive Agents). Furthermore, we use the mission planning system pRoPhEt MAS (Reactive Planning Engine for Multi-Agent Systems) to provide an intuitive interface to generate team activities. Therefore, we define the basic skills of our team with ALICA and define the desired goal states by using a logic description. Based on the skills, pRoPhEt MAS creates a valid ALICA plan, which will be executed by the team. The paper describes the basic components for communication, coordinated exploration, perception and object transportation. Finally, we evaluate the planning engine pRoPhEt MAS in the IMPERA scenario. In addition, we present further evaluation of pRoPhEt MAS in more dynamic environments.

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pRoPhEt MAS: Reactive Planning Engine for Multiagent Systems

Cited by 2 publications

References 6 publications

Toward Formal Models and Languages for Verifiable Multi-Robot Systems

Toward Formal Models and Languages for Verifiable Multi-Robot Systems

IMPERA: Integrated Mission Planning for Multi-Robot Systems

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