Intelligent agent supporting human–multi-robot team collaboration

Rosenfeld, Ariel; Agmon, Noa; Maksimov, O.; Kraus, Sarit

doi:10.1016/j.artint.2017.08.005

Cited by 76 publications

(43 citation statements)

References 28 publications

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“…Robots cooperate to develop multi-robot systems, which integrates multiple agents operating in the same environment. Such technology can develop and upgrade smart applications regarding robotic systems, remotely manage distributed activities, and increase fault tolerance, to attain an improvement of the overall system performances [ 39 ]. Furthermore, sensors and actuators can be integrated into robot applications, aiming to optimize, monitor, and control various processes such as navigation, calibration, and tuning [ 40 ].…”

Section: Smart Technologies In Industry 40mentioning

confidence: 99%

Internet of Robotic Things in Smart Domains: Applications and Challenges

Romeo

Petitti

Marani

et al. 2020

Sensors

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With the advent of the Fourth Industrial Revolution, Internet of Things (IoT) and robotic systems are closely cooperating, reshaping their relations and managing to develop new-generation devices. Such disruptive technology corresponds to the backbone of the so-called Industry 4.0. The integration of robotic agents and IoT leads to the concept of the Internet of Robotic Things, in which innovation in digital systems is drawing new possibilities in both industrial and research fields, covering several domains such as manufacturing, agriculture, health, surveillance, and education, to name but a few. In this manuscript, the state-of-the-art of IoRT applications is outlined, aiming to mark their impact on several research fields, and focusing on the main open challenges of the integration of robotic technologies into smart spaces. IoRT technologies and applications are also discussed to underline their influence in everyday life, inducing the need for more research into remote and automated applications.

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Section: Smart Technologies In Industry 40mentioning

confidence: 99%

Internet of Robotic Things in Smart Domains: Applications and Challenges

Romeo

Petitti

Marani

et al. 2020

Sensors

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“…Agent-based methodologies allow for the identification and explanation of the causes of agent interactions involved in the phenomena, providing a greater understanding of the context. Rosenfeld et al [9], proposed a methodology for using automated agents in two scenarios: real-world and human-multi robot, for collaborative tasks. The agents in this research are able to learn from past interactions, creating policies that develop deeper planning capabilities.…”

Section: Related Workmentioning

confidence: 99%

Modelling the Interaction Levels in HCI Using an Intelligent Hybrid System with Interactive Agents: A Case Study of an Interactive Museum Exhibition Module in Mexico

et al. 2018

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Technology has become a necessity in our everyday lives and essential for completing activities we typically take for granted; technologies can assist us by completing set tasks or achieving desired goals with optimal affect and in the most efficient way, thereby improving our interactive experiences. This paper presents research that explores the representation of user interaction levels using an intelligent hybrid system approach with agents. We evaluate interaction levels of Human-Computer Interaction (HCI) with the aim of enhancing user experiences. We consider the description of interaction levels using an intelligent hybrid system to provide a decision-making system to an agent that evaluates interaction levels when using interactive modules of a museum exhibition. The agents represent a high-level abstraction of the system, where communication takes place between the user, the exhibition and the environment. In this paper, we provide a means to measure the interaction levels and natural behaviour of users, based on museum user-exhibition interaction. We consider that, by analysing user interaction in a museum, we can help to design better ways to interact with exhibition modules according to the properties and behaviour of the users. An interaction-evaluator agent is proposed to achieve the most suitable representation of the interaction levels with the aim of improving user interactions to offer the most appropriate directions, services, content and information, thereby improving the quality of interaction experienced between the user-agent and exhibition-agent.

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“…Today most robotic applications are targeting for industrial production speed and quality improvement as well as for human replacement in various scenarios, which range from social-oriented human-robot interaction scenarios (Pipe et al, 2014) to dangerous for a human urban search and rescue scenarios (Magid et al, 2011). The later scenarios may include indoor and outdoor environments and require good performance in autonomous navigation within unknown environments (Indelman et al, 2015), ability to deal with computational complexity of simultaneous localization and mapping (SLAM) (Buyval et al, 2016), capabilities of negotiation and collaboration (Panov and Yakovlev, 2017) with other robots within a team (Rosenfeld et al, 2015) or swarm control (Ronzhin et al, 2016) and other functionality.…”

Section: Introductionmentioning

confidence: 99%

Modified Spline-based Path Planning for Autonomous Ground Vehicle

Magid

Lavrenov

Khasianov

2017

Proceedings of the 14th International Conference on Informatics in Control, Automation and Robotics

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Potential function based methods play significant role in global and local path planning. While these methods are characterized with good reactive behavior and implementation simplicity, they suffer from a well-known problem of getting stuck in local minima of a navigation function. In this article we propose a modification of our original spline-based path planning algorithm for a mobile robot navigation, which succeeds to solve local minima problem and adds additional criteria of start and target points visibility to help optimizing the path selection. We apply a Voronoi graph based path as an input for iterative multi criteria optimization algorithm. The algorithm was implemented in Matlab environment and simulation results demonstrate that we succeeded to overcome our original algorithm pitfalls.

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Intelligent agent supporting human–multi-robot team collaboration

Cited by 76 publications

References 28 publications

Internet of Robotic Things in Smart Domains: Applications and Challenges

Internet of Robotic Things in Smart Domains: Applications and Challenges

Modelling the Interaction Levels in HCI Using an Intelligent Hybrid System with Interactive Agents: A Case Study of an Interactive Museum Exhibition Module in Mexico

Modified Spline-based Path Planning for Autonomous Ground Vehicle

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