Grounding commonsense knowledge in intelligent systems

Daoutis, Marios; Coradeshi, Silvia; Loutfi, Amy

doi:10.3233/ais-2009-0040

Cited by 27 publications

(13 citation statements)

References 11 publications

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“…Daoutis et al [9] introduce one of the first complete architectures for grounded human-robot interaction. They successfully bind low-level percepts (including view-point independent SIFT based object recognition) to a high-level knowledge representation and reasoning system.…”

Section: Related Workmentioning

confidence: 99%

Grounding the Interaction: Anchoring Situated Discourse in Everyday Human-Robot Interaction

Lemaignan

Ros

Sisbot

et al. 2011

Int J of Soc Robotics

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20 pagesInternational audienceThis paper presents how extraction, representation and use of symbolic knowledge from real-world perception and human-robot verbal and non-verbal in-teraction can actually enable a grounded and shared model of the world that is suitable for later high-level tasks such as dialogue understanding. We show how the anchoring process itself relies on the situated nature of human-robot interactions. We present an integrated approach, including a specialized symbolic knowledge representation system based on Description Logics, and case studies on several robotic platforms that demonstrate these cognitive capabilities

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Section: Related Workmentioning

confidence: 99%

Grounding the Interaction: Anchoring Situated Discourse in Everyday Human-Robot Interaction

Lemaignan

Ros

Sisbot

et al. 2011

Int J of Soc Robotics

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“…Regarding the representation of knowledge in MAS for general purposes, one of the first works published in the journal is the paper by Daoutis et al [22]. They propose augmenting perceptual data gathered from different sensors using ontologies that define concepts such as location, spatial relations, colours, etc.…”

Section: When Multi-agent Systems Meet the Semantic Web: Representingmentioning

confidence: 99%

Artificial intelligence and ambient intelligence

Gams

Härmä

et al. 2019

AIS

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Ambient intelligence (AmI) is intrinsically and thoroughly connected with artificial intelligence (AI). Some even say that it is, in essence, AI in the environment. AI, on the other hand, owes its success to the phenomenal development of the information and communication technologies (ICTs), based on principles such as Moore's law. In this paper we give an overview of the progress in AI and AmI interconnected with ICT through information-society laws, superintelligence, and several related disciplines, such as multi-agent systems and the Semantic Web, ambient assisted living and e-healthcare, AmI for assisting medical diagnosis, ambient intelligence for e-learning and ambient intelligence for smart cities. Besides a short history and a description of the current state, the frontiers and the future of AmI and AI are also considered in the paper.

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“…In K now R ob , the abstraction of data into symbolic concepts is not performed before the data enters the knowledge base, as it is the common approach in literature (Daoutis et al, 2009; Lemaignan et al, 2010). Instead, the abstract representation is computed on demand once it is needed to answer a query.…”

Section: Knowledge Processing For Robotsmentioning

confidence: 99%

KnowRob: A knowledge processing infrastructure for cognition-enabled robots

Tenorth

Beetz

2013

The International Journal of Robotics Research

311

150

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Autonomous service robots will have to understand vaguely described tasks, such as "set the table" or "clean up". Performing such tasks as intended requires robots to fully, precisely, and appropriately parameterize their low-level control programs. We propose knowledge processing as a computational resource for enabling robots to bridge the gap between vague task descriptions and the detailed information needed to actually perform those tasks in the intended way. In this article, we introduce the KNOWROB knowledge processing system that is specifically designed to provide autonomous robots with the knowledge needed for performing everyday manipulation tasks. The system allows the realization of "virtual knowledge bases": collections of knowledge pieces that are not explicitly represented but computed on demand from the robot's internal data structures, its perception system, or external sources of information. This article gives an overview of the different kinds of knowledge, the different inference mechanisms, and interfaces for acquiring knowledge from external sources, such as the robot's perception system, observations of human activities, Web sites on the Internet, as well as Web-based knowledge bases for information exchange between robots. We evaluate the system's scalability and present different integrated experiments that show its versatility and comprehensiveness.

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Grounding commonsense knowledge in intelligent systems

Cited by 27 publications

References 11 publications

Grounding the Interaction: Anchoring Situated Discourse in Everyday Human-Robot Interaction

Grounding the Interaction: Anchoring Situated Discourse in Everyday Human-Robot Interaction

Artificial intelligence and ambient intelligence

KnowRob: A knowledge processing infrastructure for cognition-enabled robots

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