A proposal for semantic map representation and evaluation

Capobianco, Roberto; Serafin, Jacopo; Dichtl, Johann; Grisetti, Giorgio; Iocchi, Luca; Nardi, Daniele

doi:10.1109/ecmr.2015.7324198

Cited by 16 publications

(25 citation statements)

References 17 publications

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“…Semantic mapping is the incremental process of associating relevant information of the world (i.e. spatial information, temporal events, agents and actions) to a formal description supported by a reasoning engine [19], with the aim of learning to understand, collaborate and communicate. In particular, a semantic map is a representation that contains, in addition to spatial information about the environment, assignments of mapped features to entities of known classes [20].…”

Section: Semantic Mappingmentioning

confidence: 99%

“…For this reason, in Ref. [19] a formalization of a basic general structure for semantic maps is proposed, as the result of a generalization and intersection effort with respect to the representations adopted in the literature. This representation is proposed to play the role of a common interface among all the semantic maps, and can be easily extended or specialized as needed.…”

Section: Semantic Mappingmentioning

confidence: 99%

See 1 more Smart Citation

RoCKIn@Home: Domestic Robots Challenge

Iocchi¹,

Kraetzschmar²,

Nardi³

et al. 2017

RoCKIn - Benchmarking Through Robot Competitions

Self Cite

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Service robots performing complex tasks involving people in houses or public environments are becoming more and more common, and there is a huge interest from both the research and the industrial point of view. The RoCKIn@Home challenge has been designed to compare and evaluate different approaches and solutions to tasks related to the development of domestic and service robots. RoCKIn@Home competitions have been designed and executed according to the benchmarking methodology developed during the project and received very positive feedbacks from the participating teams. Tasks and functionality benchmarks are explained in detail.

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Section: Semantic Mappingmentioning

confidence: 99%

Section: Semantic Mappingmentioning

confidence: 99%

RoCKIn@Home: Domestic Robots Challenge

Iocchi¹,

Kraetzschmar²,

Nardi³

et al. 2017

RoCKIn - Benchmarking Through Robot Competitions

Self Cite

View full text Add to dashboard Cite

show abstract

“…Although there are many existing approaches to semantic representations of the environment (see [7] for a survey), a standard formalism does not exist. In this section, we thus define the main features of the knowledge base used in the project, based on experience in previous work [1,3]. We first introduce the semantic labels used to describe elements of the world, then predicates that determine relations among these labels, and finally its application to the use case in the project.…”

Section: Knowledge Base Representation and Reasoningmentioning

confidence: 99%

COACHES Cooperative Autonomous Robots in Complex and Human Populated Environments

Iocchi

Lázaro

Jeanpierre

et al. 2015

Lecture Notes in Computer Science

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The deployment of robots in dynamic, complex and uncertain environments populated by people is gaining more and more attention, from both research and application perspectives. The new challenge for the near future is to deploy intelligent social robots in public spaces to make easier and safer the use of these spaces. In this paper, we provide an overview of the COACHES project which addresses fundamental issues related to the design and development of autonomous robots to be deployed in public spaces. In particular, we describe the main components in which Artificial Intelligence techniques are used and integrated with the robotic system, as well as implementation details and some preliminary tests of these components. Public spaces in large cities are becoming increasingly complex and unwelcoming environments because of the overcrowding and complex information in signboards. It is in the interest of cities to make their public spaces easier to use, friendlier to visitors and safer to increasing elderly population and to the people with disabilities. In the last decade, we observe tremendous progress in the development of robots in dynamic environments populated by people. There are thus big expectations in the deployment of robots in public areas (malls, touristic sites, parks, etc.) to offer services to welcome people in the environment and improve its usability by visitors, elderly or disabled people. Such application domains require robots with new capabilities leading to new scientific challenges: robots should assess the situation, estimate the needs of people, socially interact in a dynamic way and in a short time, with many people, the navigation should be safe and respects the social norms. These capabilities require new skills including robust and safe navigation, robust image and video processing, short-term human-robot interaction models, human need estimation techniques and distributed and scalable multi-agent planning.

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“…Zender et al [61] and Capobianco et al [95] encoded conceptual knowledge into a Web Ontology Language-description logic (OWL-DL) ontology. In [61], a description-logic reasoner employed some situated dialogues between a robot and a user to provide new knowledge for the robot to further infer.…”

Section: Semantic Representationmentioning

confidence: 99%

“…The final map is shown in Figure 13. In [95], a standard methodology for representing and evaluating semantic maps was proposed. The formalisation consisted of a reference frame, spatial information and a set of logic predicates.…”

Section: Semantic Representationmentioning

confidence: 99%

Extracting Semantic Information from Visual Data: A Survey

Liu

et al. 2016

Robotics

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Abstract:The traditional environment maps built by mobile robots include both metric ones and topological ones. These maps are navigation-oriented and not adequate for service robots to interact with or serve human users who normally rely on the conceptual knowledge or semantic contents of the environment. Therefore, the construction of semantic maps becomes necessary for building an effective human-robot interface for service robots. This paper reviews recent research and development in the field of visual-based semantic mapping. The main focus is placed on how to extract semantic information from visual data in terms of feature extraction, object/place recognition and semantic representation methods.

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A proposal for semantic map representation and evaluation

Cited by 16 publications

References 17 publications

RoCKIn@Home: Domestic Robots Challenge

RoCKIn@Home: Domestic Robots Challenge

COACHES Cooperative Autonomous Robots in Complex and Human Populated Environments

Extracting Semantic Information from Visual Data: A Survey

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