People Management Framework Using a 2D Camera for Human-Robot Social Interactions

Saraydaryan, Jacques; Leber, Raphael; Jumel, Fabrice

doi:10.1007/978-3-030-35699-6_21

Cited by 3 publications

(2 citation statements)

References 13 publications

(13 reference statements)

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“…Saraydaryan et al propose a framework in the domestic context that collects high-level information about people. Pepper can acquire data on clothing colors, position and posture, following and analyzing people [29]. It can describe one person among the others, go towards a person who is calling it and, also, check if people are sitting, or they are pointing to something.…”

Section: A Methods Built On Peppermentioning

confidence: 99%

Contextual Trust Model With a Humanoid Robot Defense for Attacks to Smart Eco-Systems

et al. 2020

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Pepper is a humanoid robot that just embeds the few computational resources for controlling its sensors and actuators, and is not capable of handling big amounts of data or performing in parallel complicate tasks. Aiming at enriching its functionalities and its interaction with the environment, the robot has been put in communication with a plethora of satellite smart objects and services ranging from simple environmental sensors, up to deep learning enhanced smart cameras. The addition of biometric, emotional, social, machine learning and other capabilities to Pepper, while enabling advanced functionalities and additional instruments for controlling users and the environment, raises security and, obviously, privacy concerns. The robot itself, its interaction with the environment and every weakness exposed by the smart objects involved in its ecosystem, may represent an exploit point for attacking the smart home and threaten security and privacy. Aiming at preventing attacks and strengthen security, each action with the system is evaluated against the entire context, as detected by the entire eco-system of smart-objects. This paper describes and analyses the experience and how the semantic trust model adopted mitigates the effects of weaknesses and the risks related to smart home cyber-attacks.INDEX TERMS Social robots, human-robot interaction, Internet of Things, ontologies, trust model, Pepper.

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Section: A Methods Built On Peppermentioning

confidence: 99%

Contextual Trust Model With a Humanoid Robot Defense for Attacks to Smart Eco-Systems

et al. 2020

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“…Domestic robots must be able to collect various information regarding people to perform tasks and conduct socially acceptable human-robot interactions. Saraydaryan et al (114) proposed a framework for extracting high-level human features from a 2-D camera in addition to tracking people over time. Recognition of people's poses and postures, clothing colors, and faces is combined with tracking and reidentification abilities.…”

Section: Human-robot Interactionmentioning

confidence: 99%

Scientific and Technological Challenges in RoboCup

Asada

Stryk

2020

Annu. Rev. Control Robot. Auton. Syst.

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Since its inception in 1997, RoboCup has developed into a truly unique and long-standing research community advancing robotics and artificial intelligence through various challenges, benchmarks, and test fields. The main purposes of this article are to evaluate the research and development achievements so far and to identify new challenges and related new research issues. Unlike other robot competitions and research conferences, RoboCup eliminates the boundaries between pure research activities and the development of full system designs with hardware and software implementations at a site open to the public. It also creates specific scientific and technological research and development challenges to be addressed. In this article, we provide an overview of RoboCup, including its league structure and related research issues. We also review recent studies across several research categories to show how participants (called RoboCuppers) address the research and development challenges before, during, and after the annual competitions. Among the diversity of research issues, we highlight two unique aspects of the challenges: the platform design of the robots and the game evaluations. Both of these aspects contribute to solving the research and development challenges of RoboCup and verifying the results from a common perspective (i.e., a more objective view). Finally, we provide concluding remarks and discuss future research directions.

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