Agent-based Web Supported Simulation of Human-robot Collaboration

Antakli, André; Spieldenner, Torsten; Rubinstein, Dmitri; Spieldenner, Daniel; Herrmann, Erik; Sprenger, Janis; Zinnikus, Ingo

doi:10.5220/0008163000880099

Cited by 10 publications

(5 citation statements)

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“…Within this line, the field of crowd simulation has also gained strength, and we also find some studies on it using VR and MAS [57][58][59][60][61][62][63][64][65][66][67][68]. This type of simulation has multiple purposes: planning emergency plans [69][70][71][72], improvement of the work environment [73][74][75][76][77][78], improvement of the educational environment [79][80][81][82][83][84][85][86], people training [87][88][89][90][91][92][93][94][95], interactions between humans and avatars [96,97], smart buildings and commerce simulation [98,99], etc.…”

Section: Human Behaviormentioning

confidence: 99%

“…Also to improve the work environment, Zeng et al [74] proposed a platform that simulates the activity of an office building to determine and improve sedentary lifestyle at work, it is believed that the improvement in the design of these buildings can promote an active and healthy workforce. Antakli et al [75,76] proposed a framework for the 3D simulation of hybrid equipment (robots, humans, etc.) in production scenarios to evaluate the critical properties of such scenarios and the assignment of tasks to team members.…”

Section: Work Environmentmentioning

confidence: 99%

“…These applications are related to different purposes that are described and in which that section has been divided: videogames development [30][31][32][33][34][35][36][37][38][39], robot simulation [40,41], interactive virtual environments development [42][43][44][45], human behavior simulation , dissemination of cultural heritage [100,101], urban m development of autonomous vehicles [107,108], and machinery simulation [109][110][111] (Figure 5). Also, simulation of human behavior can be divided into subcategories: crowds simulation [57][58][59][60][61][62][63][64][65][66][67][68], emergency plans [69][70][71][72], work environment [73][74][75][76][77][78], educational environment…”

Section: What Applications Have Been Developed With Multi-agent Systems In the Field Of Virtual Reality?mentioning

confidence: 99%

“…In the case of the development of IVEs, frameworks were presented for their creation in which MAS serve to represent all the objects in the environment [42][43][44][45]. In the human behavior simulation, multi-agent systems are used to create different types of movements [46,47] and behaviors [48][49][50][51][52][53][54][55][56] for avatars and NPCs that are appreciated by the user as realistic so that they can be used for more serious simulations such as emergency plans [69][70][71][72], improvements of the labor [73][74][75][76][77][78] and educational [79][80][81][82][83][84][85][86] environment, personnel training [87][88][89][90][91][92][93][94][95], etc. For the dissemination of cultural heritage, MAS serve to represent people in the past as well as objects and artifacts [100,101], so that users could learn about it.…”

Section: What Applications Have Been Developed With Multi-agent Systems In the Field Of Virtual Reality?mentioning

confidence: 99%

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On the Synergy between Virtual Reality and Multi-Agent Systems

2021

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Multi-agent systems integrate a great variety of artificial intelligence techniques from different fields, these systems have made it possible to create intelligent systems more efficiently. On the other hand, virtual reality applications are accepted as viable techniques in different areas such as visualization, simulation, design, and research. The combined use of these two technologies has led to the development of realistic and interactive applications. This work aims to do a Systematic Mapping Study (SMS) relying on the guidelines of Kitchenham and Petersen to analyze the state of the art of VR applications using multi-agent systems. Inclusion and exclusion criteria have been applied to identify relevant papers, 82 articles were selected and categorized according to the publication type, the research type, the asset type, and the purpose of the work. A complete review of the 82 selected articles was performed, based on the research questions that were established. This review made it possible to clarify the open lines of research that exist and to know where research in this field can be directed.

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Section: Human Behaviormentioning

confidence: 99%

Section: Work Environmentmentioning

confidence: 99%

Section: What Applications Have Been Developed With Multi-agent Systems In the Field Of Virtual Reality?mentioning

confidence: 99%

Section: What Applications Have Been Developed With Multi-agent Systems In the Field Of Virtual Reality?mentioning

confidence: 99%

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On the Synergy between Virtual Reality and Multi-Agent Systems

2021

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“…Accessible Java Agent Nucleus (AJAN, see [25]) (https://github.com/aantakli/AJANservice (accessed on 25 October 2021)) developed at the German Research Center for Artificial Intelligence (DFKI) is a MAS to manage knowledge-based agents. AJAN was primarily developed to interact in LD environments; thus, AJAN uses RDF triplestores to store agent knowledge and SPARQL to query it.…”

Section: Orchestrating Things and Services With Ajanmentioning

confidence: 99%

Orchestrating Heterogeneous Devices and AI Services as Virtual Sensors for Secure Cloud-Based IoT Applications

Alberternst

Anisimov

Antakli

et al. 2021

Sensors

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The concept of the cloud-to-thing continuum addresses advancements made possible by the widespread adoption of cloud, edge, and IoT resources. It opens the possibility of combining classical symbolic AI with advanced machine learning approaches in a meaningful way. In this paper, we present a thing registry and an agent-based orchestration framework, which we combine to support semantic orchestration of IoT use cases across several federated cloud environments. We use the concept of virtual sensors based on machine learning (ML) services as abstraction, mediating between the instance level and the semantic level. We present examples of virtual sensors based on ML models for activity recognition and describe an approach to remedy the problem of missing or scarce training data. We illustrate the approach with a use case from an assisted living scenario.

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