Social Robots for Long-Term Interaction: A Survey

Leite, Iolanda; Martinho, Carlos; Paiva, Ana

doi:10.1007/s12369-013-0178-y

Cited by 662 publications

(490 citation statements)

References 53 publications

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“…Usually, such criteria as the ability to get and hold the user's attention to the 20 proposed service, evaluated through direct observation, are used to assess the quality of the social interaction between robots and people [29]. Several studies have focused on the underlying reasons for the acceptance of social robots in different scenarios; their usefulness, adaptability, enjoyment, sociability, companionship or perceived behavioral control have been identified as important 25 parameters for potential users' acceptance [22].…”

Section: Introductionmentioning

confidence: 99%

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Long-term assessment of a service robot in a hotel environment

Pinillos

Marcos

Feliz

et al. 2016

Robotics and Autonomous Systems

137

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The long term evaluation of the Sacarino robot is presented in this paper. This study aimed to improve the robot's capabilities as a bellboy in a hotel; walking alongside the guests, providing information about the city and the hotel and providing hotel-related services. The paper establishes a three-stage assessment methodology based on the continuous measurement of a set of metrics regarding navigation and interaction with guests. Sacarino has been automatically collecting information in a real hotel environment for long periods of time. The acquired information has been analyzed and used to improve the robot's operation in the hotel through successive refinements. Some interesting considerations and useful hints for the researchers of service robots have been extracted from the analysis of the results.

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Section: Introductionmentioning

confidence: 99%

“…A wider survey that addresses the particularities of prolonged interactions 65 with robots can be seen in [20]. This survey addresses a total of 24 papers organized by their application domain: Health Care and Therapy, Education, Work Environments and Public Spaces, and the Home.…”

Section: Introductionmentioning

confidence: 99%

Long-term assessment of a service robot in a hotel environment

Pinillos

Marcos

Feliz

et al. 2016

Robotics and Autonomous Systems

137

View full text Add to dashboard Cite

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“…The need of implementing Adaptive Robot Interfaces (ARIs) or Adaptive Social Robots (ASRs) has also been emphasised in HRI literature [5,6]. Before an ASR or an ARI is defined, it is important to distinguish between an autonomous robot and an adaptive robot.…”

Section: Introductionmentioning

confidence: 99%

“…These social domains includes education [10], public places [5], domestic and work environments [5], health care and therapy [11]. We also find a number of research studies that have been conducted on understanding how a user interacts with a robot, or what is an effect of robot's social behaviour [12], role [13], anthropomorphism, animacy, like-ability, perceived intelligence and perceived safety on user's perception [14] in various environments.…”

Section: Introductionmentioning

confidence: 99%

A Systematic Review of Adaptivity in Human-Robot Interaction

Ahmad

Mubin

Orlando

2017

MTI

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Abstract:As the field of social robotics is growing, a consensus has been made on the design and implementation of robotic systems that are capable of adapting based on the user actions. These actions may be based on their emotions, personality or memory of past interactions. Therefore, we believe it is significant to report a review of the past research on the use of adaptive robots that have been utilised in various social environments. In this paper, we present a systematic review on the reported adaptive interactions across a number of domain areas during Human-Robot Interaction and also give future directions that can guide the design of future adaptive social robots. We conjecture that this will help towards achieving long-term applicability of robots in various social domains.

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“…Expectations from social robots are high, since they must successfully assist the users with daily tasks while maintaining their engagement in interaction over extended periods of time [1]. One way to achieve this is by enabling the robots to learn from the interaction with the users [2].…”

Section: Introductionmentioning

confidence: 99%

User Evaluation of an Interactive Learning Framework for Single-Arm and Dual-Arm Robots

et al. 2016

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Abstract. Social robots are expected to adapt to their users and, like their human counterparts, learn from the interaction. In our previous work, we proposed an interactive learning framework that enables a user to intervene and modify a segment of the robot arm trajectory. The framework uses gesture teleoperation and reinforcement learning to learn new motions. In the current work, we compared the user experience with the proposed framework implemented on the single-arm and dual-arm Barrett's 7-DOF WAM robots equipped with a Microsoft Kinect camera for user tracking and gesture recognition. User performance and workload were measured in a series of trials with two groups of 6 participants using two robot settings in different order for counterbalancing. The experimental results showed that, for the same task, users required less time and produced shorter robot trajectories with the single-arm robot than with the dual-arm robot. The results also showed that the users who performed the task with the single-arm robot first experienced considerably less workload in performing the task with the dual-arm robot while achieving a higher task success rate in a shorter time.

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Social Robots for Long-Term Interaction: A Survey

Cited by 662 publications

References 53 publications

Long-term assessment of a service robot in a hotel environment

Long-term assessment of a service robot in a hotel environment

A Systematic Review of Adaptivity in Human-Robot Interaction

User Evaluation of an Interactive Learning Framework for Single-Arm and Dual-Arm Robots

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