Collective Grounded Representations for Robots

Hugues, Louis

doi:10.1007/978-4-431-67919-6_8

Cited by 7 publications

(6 citation statements)

References 4 publications

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“…An abstract (however still unsatisfactory) approach was proposed by Kramer and Magee (2007) [25] as the software engineering point of view of the problem. The idea of Jung and Zelinsky (2000) [26], and Hugues (2000) [27] of common grounded symbolic communication between heterogeneous cooperating robots is very close to the concept of common ontology, however, it was not fully developed and not continued. An interesting approach to composite services (heterogeneous robot teams) as temporal organizations with elements of recovery from failures was presented in Zhong and DeLoach (2011) [28].…”

Section: Motivations and Related Workmentioning

confidence: 99%

SO-MRS: A Multi-robot System Architecture Based on the SOA Paradigm and Ontology

Skarzynski

Stępniak

Bartyna

et al. 2018

Towards Autonomous Robotic Systems

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A generic architecture for a class of distributed robotic systems is presented. The architecture supports openness and heterogeneity, i.e. heterogeneous components may be joined and removed from the systems without affecting its basic functionality. The architecture is based on the paradigm of Service Oriented Architecture (SOA), and a generic representation (ontology) of the environment. A device (e.g. robot) is seen as a collection of its capabilities exposed as services. Generic protocols for publishing, discovering, arranging services are proposed for creating composite services that can accomplish complex tasks in an automatic way. Also generic protocols for execution of composite services are proposed along with simple protocols for monitoring the executions, and for recovery from failures. A software platform built on a multi-robot system (according to the proposed architecture) is a multi-agent system.

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Section: Motivations and Related Workmentioning

confidence: 99%

SO-MRS: A Multi-robot System Architecture Based on the SOA Paradigm and Ontology

Skarzynski

Stępniak

Bartyna

et al. 2018

Towards Autonomous Robotic Systems

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“…It is this fact that stands at the basis of our proposed methods. More recent work in multi robot communication has focused on representations of languages and the grounding of these representations in the physical world [21,22].…”

Section: Communication Models and Pheromonesmentioning

confidence: 99%

Multi-agent Physical A* with Large Pheromones

Felner

Shoshani

Wagner

et al. 2005

Auton Agent Multi-Agent Syst

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Physical A* (PHA*) and its multi-agent version MAPHA* are algorithms that find the shortest path between two points in an unknown real physical environment with one or many mobile agents [A. Felner et al. Previous work assumed a complete sharing of knowledge between agents. Here we apply this algorithm to a more restricted model of communication which we call large pheromones, where agents communicate by writing and reading data at nodes of the graph that constitutes their environment. Previous works on pheromones usually assumed that only a limited amount of data can be written at each node. The large pheromones model assumes no limitation on the size of the pheromones and thus each agent can write its entire knowledge at a node. We show that with this model of communication the behavior of a multi-agent system is almost as good as with complete knowledge sharing. Under this model we also introduce a new type of agent, a communication agent, that is responsible for spreading the knowledge among other agents by moving around the graph and copying pheromones. Experimental results show that the contribution of communication agents is rather limited as data is already spread to other agents very well with large pheromones.

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“…Behaviors like flocking, formation maintenance or map building [6,39,22,20,45] are, thus, part of the same task class. In the exploration task there is the need to distribute the robots as sparsely as possible so that the information they can collect does not overlap, while in the flocking task the goal is that the robotic agents move around together, such as in a flock.…”

Section: Exploration and Flockingmentioning

confidence: 99%

“…In [22] an exploration task in a office like environment is used to test a distributed, reactive MRS, designed to study the problem of grounding representations and communications of the robotic agents in real perceptions. The approach is strongly coordinated since, even though the robots are not coordinated for navigation, a protocol for exchanging representations of perceptual data is used.…”

Section: Exploration and Flockingmentioning

confidence: 99%

“…In [6] the MRS is not coordinated and thus it is classified as reactive since its robotic agents execute their task by filling the gaps available in the formation, without communicating with each other. The work in [22] tests the possibility to realize a grounded language within the team, so it is not important to implement a MRS that presents a social deliberative behavior. Each team member can react to environmental changes by taking individual decisions without any necessity to reorganize the entire system strategy, while strong coordination is an essential property to realize the common grounded knowledge base.…”

Section: Exploration and Flockingmentioning

confidence: 99%

See 1 more Smart Citation

Reactivity and Deliberation: A Survey on Multi-Robot Systems

Iocchi

Nardi

Salerno

2001

Balancing Reactivity and Social Deliberation in Multi-Agent Systems

103

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Abstract. Multi Robot Systems are, nowadays, an important research area within Robotics and Artificial Intelligence. Although Multi Robot Systems can be regarded as a particular case of Multi Agent Systems, it seems appropriate to study the Multi Robot Systems from a specific viewpoint, because of the issues which arise from the embodiment of agents operating in real environments. In this paper, we present an analysis of Multi Robot Systems by looking at their cooperative aspects. In particular, we propose a taxonomy of Multi Robot Systems and a characterization of reactive and social deliberative behaviors of the Multi Robot System as a whole. Finally, we address some Multi Robot Systems, which we consider representative of the various nodes in our taxonomy.

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Collective Grounded Representations for Robots

Cited by 7 publications

References 4 publications

SO-MRS: A Multi-robot System Architecture Based on the SOA Paradigm and Ontology

SO-MRS: A Multi-robot System Architecture Based on the SOA Paradigm and Ontology

Multi-agent Physical A* with Large Pheromones

Reactivity and Deliberation: A Survey on Multi-Robot Systems

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