Recent trends in social aware robot navigation: A survey

Charalampous, Konstantinos; Kostavelis, Ioannis; Γαστεράτος, Αντώνιος

doi:10.1016/j.robot.2017.03.002

Cited by 156 publications

(85 citation statements)

References 48 publications

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“…For our research, we leverage both definitions and define trust in AVs as the willingness of an individual to be vulnerable to the actions of an AV based on the attitude that the AV will help them achieve their goals. Trust in an autonomous vehicle has been identified as a vital determinant of whether the driver will employ an autonomous vehicle (Beller, Heesen, and Vollrath 2013;Charalampous, Kostavelis, and Gasteratos 2017;Verberne, Ham, and Midden 2012;Xiong et al 2012).…”

Section: Trust In Automationmentioning

confidence: 99%

Situational Awareness, Driver’s Trust in Automated Driving Systems and Secondary Task Performance

Petersen¹,

Robert²,

Yang³

et al. 2019

SAE Intl. J CAV

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Driver assistance systems, also called automated driving systems, allow drivers to immerse themselves in non-driving-related tasks. Unfortunately, drivers may not trust the automated driving system, which prevents either handing over the driving task or fully focusing on the secondary task. We assert that enhancing situational awareness can increase a driver's trust in automation. Situational awareness should increase a driver's trust and lead to better secondary task performance. This study manipulated driversʼ situational awareness by providing them with different types of information: the control condition provided no information to the driver, the low condition provided a status update, while the high condition provided a status update and a suggested course of action. Data collected included measures of trust, trusting behavior, and task performance through surveys, eye-tracking, and heart rate data. Results show that situational awareness both promoted and moderated the impact of trust in the automated vehicle, leading to better secondary task performance. This result was evident in measures of self-reported trust and trusting behavior.

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Section: Trust In Automationmentioning

confidence: 99%

Situational Awareness, Driver’s Trust in Automated Driving Systems and Secondary Task Performance

Petersen¹,

Robert²,

Yang³

et al. 2019

SAE Intl. J CAV

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“…The derived map serves in quantifying complex social proxemics cues (see [4] for a recent survey) that robots can exploit to optimize their responses in initiating or avoiding an interaction (see Fig. 6).…”

Section: Human Activity Understanding and Compliant Operationmentioning

confidence: 99%

System Design for Coordinated Multi-robot Assistance Deployment in Smart Spaces

Papadakis

Lohr

Lujak

et al. 2018

2018 Second IEEE International Conference on Robotic Computing (IRC)

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Abstract-In this work, we set the bases of the integration of ambient intelligence (AmI) with mobile robot teams (MRT), aiming to enhance ambient assisted living services addressing a variety of tasks. We argue that people with reduced mobility can benefit from a synergy between AmI and MRT in various aspects. Towards this direction, we identify principal functionalities such an integrated system should provide in connection to relevant previous works and the way by which synergy could be accomplished, from low-level behavioural to higher-level task planning of a multi-layered system architecture.

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“…The term "proxemics" was introduced here, referring to the measurement of social, personal and intimate distance and how it differs across cultures and situations. Social roboticists refer to this work when they try to implement proxemics in robotic systems, as robots should understand how close they can get to the human counterpart for an effective interaction [60]. Finally, machines and mindlessness by Nass, C., coauthor of the media equation, explores how individuals apply gender and ethnic stereotypes to computer agents and also explores the topic of anthropomorphism.…”

Section: Source Indicator Total Inside Outsidementioning

confidence: 99%

Bibliometric Analysis of Social Robotics Research: Identifying Research Trends and Knowledgebase

Mejía

Kajikawa

2017

Applied Sciences

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Abstract:As robotics becomes ubiquitous, there is increasing interest in understanding how to develop robots that better respond to social needs, as well as how robotics impacts society. This is evidenced by the growing rate of publications on social robotics. In this article, we analyze the citation network of academic articles on social robotics to understand its structure, reveal research trends and expose its knowledgebase. We found eight major clusters, namely robots as social partners, human factors and ergonomics on human robot interaction, robotics for children's development, swarm robotics, emotion detection, assessment of robotic surgery, robots for the elderly and telepresence and human robot interaction in rescue robots. In addition, despite its social focus, social science literature as a source of knowledge is barely present. Research trends point to studies on applications, rather than to specific technologies or morphologies, and in particular, towards robots as partners, for child development and assistance for the elderly.

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Recent trends in social aware robot navigation: A survey

Cited by 156 publications

References 48 publications

Situational Awareness, Driver’s Trust in Automated Driving Systems and Secondary Task Performance

Situational Awareness, Driver’s Trust in Automated Driving Systems and Secondary Task Performance

System Design for Coordinated Multi-robot Assistance Deployment in Smart Spaces

Bibliometric Analysis of Social Robotics Research: Identifying Research Trends and Knowledgebase

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