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Robot Theory of Mind with Reverse Psychology 机器人心理理论与逆向心理学
IF 5.1 Q2 Computer Science Pub Date : 2023-03-13 DOI: 10.1145/3568294.3580144
Chuang Yu, Baris Serhan, M. Romeo, A. Cangelosi
Theory of mind (ToM) corresponds to the human ability to infer other people's desires, beliefs, and intentions. Acquisition of ToM skills is crucial to obtain a natural interaction between robots and humans. A core component of ToM is the ability to attribute false beliefs. In this paper, a collaborative robot tries to assist a human partner who plays a trust-based card game against another human. The robot infers its partner's trust in the robot's decision system via reinforcement learning. Robot ToM refers to the ability to implicitly anticipate the human collaborator's strategy and inject the prediction into its optimal decision model for a better team performance. In our experiments, the robot learns when its human partner does not trust the robot and consequently gives recommendations in its optimal policy to ensure the effectiveness of team performance. The interesting finding is that the optimal robotic policy attempts to use reverse psychology on its human collaborator when trust is low. This finding will provide guidance for the study of a trustworthy robot decision model with a human partner in the loop.
心理理论(ToM)对应于人类推断他人欲望、信仰和意图的能力。习得ToM技能对于实现机器人与人之间的自然互动至关重要。ToM的一个核心组件是对错误信念进行归因的能力。在本文中,一个协作机器人试图帮助一个人类伙伴与另一个人进行基于信任的纸牌游戏。机器人通过强化学习来推断其伙伴对机器人决策系统的信任。机器人ToM指的是能够隐式地预测人类合作者的策略,并将预测注入其最优决策模型中,以获得更好的团队绩效。在我们的实验中,机器人在人类伙伴不信任它的时候进行学习,并给出最优策略建议,以确保团队绩效的有效性。有趣的发现是,当信任度较低时,最佳机器人策略试图对人类合作者使用逆向心理。这一发现将为具有人类伙伴的可信赖机器人决策模型的研究提供指导。
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引用次数: 1
Creative AI for HRI Design Explorations 为HRI设计探索创造AI
IF 5.1 Q2 Computer Science Pub Date : 2023-03-13 DOI: 10.1145/3568294.3580035
Marius Hoggenmueller, M. Lupetti, Willem van der Maden, Kazjon Grace
Design fixation, a phenomenon describing designers' adherence to pre-existing ideas or concepts that constrain design outcomes, is particularly prevalent in human-robot interaction (HRI), for example, due to collectively held and stabilised imaginations of what a robot should look like or behave. In this paper, we explore the contribution of creative AI tools to overcome design fixation and enhance creative processes in HRI design. In a four weeks long design exploration, we used generative text-to-image models to ideate and visualise robotic artefacts and robot sociotechnical imaginaries. We exchanged results along with reflections through a digital postcard format. We demonstrate the usefulness of our approach to imagining novel robot concepts, surfacing existing assumptions and robot stereotypes, and situating robotic artefacts in context. We discuss the contribution to designerly HRI practices and conclude with lessons learnt for using creative AI tools as an emerging design practice in HRI research and beyond.
设计固定,一种描述设计师坚持预先存在的想法或概念的现象,这些想法或概念限制了设计结果,在人机交互(HRI)中特别普遍,例如,由于对机器人应该是什么样子或行为的集体持有和稳定的想象。在本文中,我们探讨了创造性人工智能工具在克服设计固定和增强HRI设计创造性过程中的贡献。在为期四周的设计探索中,我们使用生成文本到图像模型来构思和可视化机器人人工制品和机器人社会技术想象。我们通过数字明信片的形式交换了结果和感想。我们证明了我们的方法在想象新的机器人概念、揭示现有的假设和机器人刻板印象以及将机器人人工制品置于环境中的有用性。我们讨论了对设计师型人力资源研究所实践的贡献,并总结了在人力资源研究所研究及其他领域使用创造性人工智能工具作为新兴设计实践的经验教训。
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引用次数: 2
PLATYPUS 鸭嘴兽
IF 5.1 Q2 Computer Science Pub Date : 2023-03-13 DOI: 10.1145/3568294.3580102
Jose Pablo De la Rosa Gutierrez, A. S. Sørensen
When robots are used for physical therapy, programming becomes too important to be left to programmers. Developing programs for training robots is time-consuming and requires expertise within multiple engineering domains, combined with physical training, therapy, and human interaction competencies. In this paper, we present Platypus: an end-user development environment that encompasses the design and execution of custom activities for robot-assisted physical training. The current version ships a set of plugins for Eclipse's IDE and uses a block-based visual language to specify the robot's behaviors at a high abstraction level, which are translated into the low-level code specifications followed by the robot. As a use case, we present its implementation on RoboTrainer, a modular, rope-based pulling device for training at home. While user tests suggest that the platform has the potential to reduce the technical obstacles for building custom training scenarios, informational and design learning barriers were revealed during the tests.
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引用次数: 1
Stretch to the Client; Re-imagining Interfaces 延伸到客户端;一次接口
IF 5.1 Q2 Computer Science Pub Date : 2023-03-13 DOI: 10.1145/3568294.3580212
Kay N. Wojtowicz, M. E. Cabrera
This paper presents the efforts made towards the creation of a client interface to be used with Hello-Robot Stretch. The goal is to create an interface that is accessible to allow for the best user experience. This interface enables users to control Stretch with basic commands through several modalities. To make this interface accessible, a simple and clear web interface was crafted so users of differing abilities can successfully interact with Stretch. A voice activated option was also added to further increase the range of possible interactions.
本文介绍了为创建与Hello-Robot Stretch一起使用的客户端界面所做的努力。目标是创建一个可访问的界面,以实现最佳的用户体验。该界面使用户能够通过几种方式控制基本命令的拉伸。为了使这个界面易于访问,设计了一个简单明了的web界面,以便不同能力的用户可以成功地与Stretch进行交互。还增加了语音激活选项,以进一步增加可能的交互范围。
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引用次数: 0
The Influence of a Robot Recommender System on Impulse Buying Tendency 机器人推荐系统对冲动购买倾向的影响
IF 5.1 Q2 Computer Science Pub Date : 2023-03-13 DOI: 10.1145/3568294.3580171
Ching-Chih Tsao, Cheng-Yi Tang, Yu-Wen Chang, Y. Sung, S. Chien, Szu-Yin Lin
The present study examines the influences of a robot recommender system on human impulse buying tendency in online e-commerce contexts. An empirical user study was conducted, where different marketing strategies (limited quantity vs. discount rate) were applied to the products and intimate designs were utilized for the robotic agent. An electroencephalogram (EEG) headset was used to capture users' brain activities, which allowed us to investigate participants' real-time cognitive perceptions toward different experimental conditions (i.e., marketing plans and robotic agents). Our preliminary results reveal that marketing strategies and robot recommender applications can trigger impulsive buying behavior and contribute to different cognitive activities.
本研究考察了机器人推荐系统对在线电子商务环境下人类冲动购买倾向的影响。对用户进行了实证研究,对产品采用了不同的营销策略(限量vs折扣率),并对机器人代理采用了亲密设计。使用脑电图(EEG)耳机捕捉用户的大脑活动,这使我们能够调查参与者对不同实验条件(即营销计划和机器人代理)的实时认知感知。我们的初步研究结果表明,营销策略和机器人推荐应用程序可以触发冲动购买行为,并有助于不同的认知活动。
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引用次数: 1
Investigating the Integration of Human-Like and Machine-Like Robot Behaviors in a Shared Elevator Scenario 研究共享电梯场景中类人与类机器机器人行为的集成
IF 5.1 Q2 Computer Science Pub Date : 2023-03-13 DOI: 10.1145/3568162.3576974
Danilo Gallo, P. Bioche, J. Willamowski, T. Colombino, Shreepriya Gonzalez-Jimenez, Herve Poirier, Cécile Boulard
This paper examines the advantages and disadvantages of combining Human-Like and Machine-Like behaviors for a robot taking a shared elevator with a bystander as part of an office delivery service scenario. We present findings of an in-person wizard-of-oz experiment that builds on and implements behavior policies developed in a previous study. In this experiment, we found that the combination of Machine-Like and Human-Like behaviors was perceived as better than Human-Like behaviors alone. We discuss possible reasons and point to key capabilities that a socially competent robot should have to achieve better Human-Like behaviors in order to seamlessly negotiate a social encounter with bystanders in a shared elevator or similar scenario. We found that establishing and maintaining a shared transactional space is one of these key requirements.
本文研究了在办公递送服务场景中,机器人与旁观者乘坐共享电梯时,将类人行为与类机器行为相结合的优缺点。我们提出了一项基于并实施先前研究中制定的行为政策的现场巫师实验的发现。在这个实验中,我们发现类机器行为和类人行为的结合被认为比单独的类人行为更好。我们讨论了可能的原因,并指出了具有社交能力的机器人应该具备的关键能力,以实现更好的类人行为,以便在共享电梯或类似场景中无缝地与旁观者进行社交接触。我们发现,建立和维护共享事务空间是这些关键需求之一。
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引用次数: 0
Open-source Natural Language Processing on the PAL Robotics ARI Social Robot 开源自然语言处理的PAL机器人ARI社交机器人
IF 5.1 Q2 Computer Science Pub Date : 2023-03-13 DOI: 10.1145/3568294.3580041
S. Lemaignan, S. Cooper, Raquel Ros, L. Ferrini, Antonio Andriella, Aina Irisarri
We demonstrate how state-of-art open-source tools for automatic speech recognition (vosk) and dialogue management (rasa) can be integrated on a social robotic platform (PAL Robotics' ARI robot) to provide rich verbal interactions. Our open-source, ROS-based pipeline implements the ROS4HRI standard, and the demonstration specifically presents the details of the integration, in a way that will enable attendees to replicate it on their robots. The demonstration takes place in the context of assistive robotics and robots for elderly care, two application domains with unique interaction challenges, for which, the ARI robot has been designed and extensively tested in real-world settings.
我们展示了如何将最先进的自动语音识别(vosk)和对话管理(rasa)的开源工具集成到社交机器人平台(PAL Robotics的ARI机器人)上,以提供丰富的语言交互。我们的开源、基于ros的管道实现了ROS4HRI标准,演示特别展示了集成的细节,使与会者能够在他们的机器人上复制它。该演示是在辅助机器人和老年护理机器人的背景下进行的,这两个应用领域具有独特的交互挑战,ARI机器人已经被设计并在现实环境中进行了广泛的测试。
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引用次数: 1
A Multimodal Dataset for Robot Learning to Imitate Social Human-Human Interaction 机器人学习模仿社会人际互动的多模态数据集
IF 5.1 Q2 Computer Science Pub Date : 2023-03-13 DOI: 10.1145/3568294.3580080
Nguyen Tan Viet Tuyen, A. Georgescu, Irene Di Giulio, O. Çeliktutan
Humans tend to use various nonverbal signals to communicate their messages to their interaction partners. Previous studies utilised this channel as an essential clue to develop automatic approaches for understanding, modelling and synthesizing individual behaviours in human-human interaction and human-robot interaction settings. On the other hand, in small-group interactions, an essential aspect of communication is the dynamic exchange of social signals among interlocutors. This paper introduces LISI-HHI - Learning to Imitate Social Human-Human Interaction, a dataset of dyadic human inter- actions recorded in a wide range of communication scenarios. The dataset contains multiple modalities simultaneously captured by high-accuracy sensors, including motion capture, RGB-D cameras, eye trackers, and microphones. LISI-HHI is designed to be a benchmark for HRI and multimodal learning research for modelling intra- and interpersonal nonverbal signals in social interaction contexts and investigating how to transfer such models to social robots.
人类倾向于使用各种非语言信号向他们的互动伙伴传达他们的信息。先前的研究利用这一渠道作为开发自动方法的基本线索,用于理解、建模和合成人机交互和人机交互设置中的个人行为。另一方面,在小组互动中,交流的一个重要方面是对话者之间社会信号的动态交换。本文介绍了LISI-HHI - Learning to imitation Social human - human Interaction,这是一个记录在各种交流场景中的二元人类交互行为的数据集。该数据集包含由高精度传感器同时捕获的多种模式,包括动作捕捉、RGB-D相机、眼动仪和麦克风。lis - hhi旨在成为HRI和多模态学习研究的基准,用于对社会互动环境中的内部和人际非语言信号进行建模,并研究如何将这些模型转移到社交机器人中。
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引用次数: 2
Coming In! Communicating Lane Change Intent in Autonomous Vehicles 进来!自动驾驶汽车的变道意图沟通
IF 5.1 Q2 Computer Science Pub Date : 2023-03-13 DOI: 10.1145/3568294.3580113
Seong Hee Lee, Nicholas Britten, Avram Block, A. Pandya, Malte F. Jung, Paul Schmitt
Lane changes of autonomous vehicles (AV) should not only succeed in making the maneuver but also provide a positive interaction experience for other drivers. As lane changes involve complex interactions, identification of a set of behaviors for autonomous vehicle lane change communication can be difficult to define. This study investigates different movements communicating AV lane change intent in order to identify which effectively communicates and positively affects other drivers' decisions. We utilized a virtual reality environment wherein 14 participants were each placed in the driver's seat of a car and experienced four different AV lane change signals. Our findings suggest that expressive lane change behaviors such as lateral movement have high levels of legibility at the cost of high perceived aggressiveness. We propose further investigation into how balancing key parameters of lateral movement can balance in legibility and aggressiveness that provide the best AV interaction experience for human drivers
自动驾驶汽车(AV)的变道不仅要成功地进行机动,还要为其他驾驶员提供积极的交互体验。由于变道涉及复杂的相互作用,很难确定自动驾驶汽车变道通信的一系列行为。本研究调查了不同的自动驾驶汽车变道意图,以确定哪些动作能有效地沟通并积极影响其他司机的决定。我们利用了一个虚拟现实环境,其中14名参与者每人坐在一辆汽车的驾驶座上,体验四种不同的自动驾驶变道信号。我们的研究结果表明,表达性变道行为,如横向移动,具有高水平的易读性,以高感知攻击性为代价。我们建议进一步研究如何平衡横向运动的关键参数来平衡易读性和攻击性,从而为人类驾驶员提供最佳的自动驾驶交互体验
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引用次数: 1
Development of a Wearable Robot that Moves on the Arm to Support the Daily Life of the User 一种可穿戴机器人的开发,它可以在手臂上移动,以支持用户的日常生活
IF 5.1 Q2 Computer Science Pub Date : 2023-03-13 DOI: 10.1145/3568294.3579983
Koji Kimura, F. Tanaka
Wearable robots can maintain physical contact with the user and interact with them to assist in daily life. However, since most wearable robots operate at a single point on the user's body, the user must be constantly aware of their presence. This imposes a burden on the user, both physically and mentally, and prevents them from wearing the robot daily. One solution to this problem is for the robot to move around the user's body. When the user does not interact with the robot, it can move to an unobtrusive position and attract less attention from the user. This research aims to develop a wearable robot that reduces the burden by developing an arm movement mechanism for wearable robots and a self-localization method for autonomous movement and helps the user's daily life by providing supportive interactions.
可穿戴机器人可以与用户保持身体接触,并与用户互动,协助日常生活。然而,由于大多数可穿戴机器人在用户身体上的一个点上操作,用户必须时刻意识到它们的存在。这给使用者带来了身体和精神上的负担,使他们无法每天佩戴机器人。解决这个问题的一个办法是让机器人绕着用户的身体移动。当用户不与机器人互动时,机器人可以移动到一个不显眼的位置,从而减少用户的注意力。本研究旨在开发可穿戴机器人,通过开发可穿戴机器人的手臂运动机构和自主运动的自我定位方法来减轻负担,并通过提供支持性交互来帮助用户的日常生活。
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引用次数: 0
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ACM Transactions on Human-Robot Interaction
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