Evaluation of social robot navigation inherently requires human input due to its qualitative nature. Motivated by the need to scale human evaluation, we propose a general method for deploying interactive, rich-client robotic simulations on the web. Prior approaches implement specific web-compatible simulators or provide tools to build a simulator for a specific study. Instead, our approach builds on standard Linux tools to share a graphical desktop with remote users. We leverage these tools to deploy simulators on the web that would typically be constrained to desktop computing environments. As an example implementation of our approach, we introduce the SEAN Experimental Platform (SEAN-EP). With SEAN-EP, remote users can virtually interact with a mobile robot in the Social Environment for Autonomous Navigation, without installing any software on their computer or needing specialized hardware. We validated that SEAN-EP could quickly scale the collection of human feedback and its usability through an online survey. In addition, we compared human feedback from participants that interacted with a robot using SEAN-EP with feedback obtained through a more traditional video survey. Our results suggest that human perceptions of robots may differ based on whether they interact with the robots in simulation or observe them in videos. Also, they suggest that people perceive the surveys with interactive simulations as less mentally demanding than video surveys.
The University of Sheffield（谢菲尔德大学）；University of Manchester（曼彻斯特大学）
There is an increasing interest in considering, implementing, and measuring trust in human-robot interaction (HRI). Typically, this centres on influencing user trust within the framing of HRI as a dyadic interaction between robot and user. We propose this misses a key complexity: a robot's trustworthiness may also be contingent on the user's relationship with, and opinion of, the individual or organisation deploying the robot. Our new HRI triad model (User, Robot, Deployer), offers novel predictions for considering and measuring trust more completely.
The aim of this workshop is to foster the exchange of insights on past and ongoing research towards effective and long-lasting collaborations between humans and robots. This workshop will provide a forum for representatives from academia and industry communities to analyse the different aspects of HRI that impact on its success. We particularly focus on AI techniques required to implement autonomous and proactive interactions, on the factors that enhance, undermine, or recover humans' acceptance and trust in robots, and on the potential ethical and legal concerns related to the deployment of s…
UT Austin（德克萨斯大学奥斯汀分校）；Samsung Research of America（三星美国研究院）；Smart Information Flow Technologies（智能信息流技术公司）；Sapienza University of Rome（罗马大学）；University of Leeds（利兹大学）；Heriot-Watt University（赫瑞-瓦特大学）；Semio；Plymouth University（普利茅斯大学）；Tufts University（塔夫茨大学）；Lund University（隆德大学）；Colorado School of Mines（科罗拉多矿业学院）
The past few years have seen rapid progress in the development of service robots. Universities and companies alike have launched major research efforts toward the deployment of ambitious systems designed to aid human operators performing a variety of tasks. These robots are intended to make those who may otherwise need to live in assisted care facilities more independent, to help workers perform their jobs, or simply to make life more convenient. Service robots provide a powerful platform on which to study Artificial Intelligence (AI) and Human-Robot Interaction (HRI) in the real world. Resear…
University of Pennsylvania（宾夕法尼亚大学）；Semio AI, Inc.（Semio AI公司）；USC（南加州大学）
Hardware platforms for socially interactive robotics can be limited by cost or lack of functionality. This paper presents the overall system -- design, hardware, and software -- for Quori, a novel, affordable, socially interactive humanoid robot platform for facilitating non-contact human-robot interaction (HRI) research. The design of the system is motivated by feedback sampled from the HRI research community. The overall design maintains a balance of affordability and functionality. Initial Quori testing and a six-month deployment are presented. Ten Quori platforms have been awarded to a div…
Robot capabilities are maturing across domains, from self-driving cars, to bipeds and drones. As a result, robots will soon no longer be confined to safety-controlled industrial settings; instead, they will directly interact with the general public. The growing field of Human-Robot Interaction (HRI) studies various aspects of this scenario - from social norms to joint action to human-robot teams and more. Researchers in HRI have made great strides in developing models, methods, and algorithms for robots acting with and around humans, but these "computational HRI" models and algorithms generall…
ERR@HRI 2024 Challenge: Multimodal Detection of Errors and Failures in Human-Robot Interactions
Politecnico di Milano（米兰理工大学）；University of Cambridge（剑桥大学）；Cornell University（康奈尔大学）；Johns Hopkins University（约翰斯·霍普金斯大学）；Cankaya University（恰卡亚大学）；Cornell Tech（康奈尔科技学院）
Over the last years, social robots have been deployed in public environments making evident the need of human-aware navigation capabilities. In this regard, the robotics community have made efforts to include proxemics or social conventions within the navigation approaches. Nevertheless, few works have tackled the problem of labelling humans as an interactive agent when blocking the robot motion trajectory. Current state of the art navigation planners will either propose an alternative path or freeze the motion until the path is free. We present the first prototype of a framework designed to e…
Czech Technical University in Prague（布拉格捷克理工大学）；Czech Institute of Informatics, Robotics, and Cybernetics（捷克信息学、机器人学与控制论研究所）
So-called collaborative robots are a current trend in industrial robotics. However, they still face many problems in practical application such as reduced speed to ascertain their collaborativeness. The standards prescribe two regimes: (i) speed and separation monitoring and (ii) power and force limiting, where the former requires reliable estimation of distances between the robot and human body parts and the latter imposes constraints on the energy absorbed during collisions prior to robot stopping. Following the standards, we deploy the two collaborative regimes in a single application and s…
HiSync: Spatio-Temporally Aligning Hand Motion from Wearable IMU and On-Robot Camera for Command Source Identification in Long-Range HRI
Department of Computer Science；Technology, BNRist Tsinghua University Beijing China；Technology, BNRist, College of AI Tsinghua University Beijing China；Technology Tsinghua University Beijing China；Beijing University of Posts；Academy of Arts \& Design Tsinghua University Beijing China；Qinghai University Xining China；Tsinghua University；Technology, BNRist, College of AI；Technology Tsinghua University；Academy of Arts \& Design Tsinghua University；Qinghai University
For a robot to repair its own error, it must first know it has made a mistake. One way that people detect errors is from the implicit reactions from bystanders -- their confusion, smirks, or giggles clue us in that something unexpected occurred. To enable robots to detect and act on bystander responses to task failures, we developed a novel method to elicit bystander responses to human and robot errors. Using 46 different stimulus videos featuring a variety of human and machine task failures, we collected a total of 2452 webcam videos of human reactions from 54 participants. To test the viabil…
Mobile robots are increasingly populating homes, hospitals, shopping malls, factory floors, and other human environments. Human society has social norms that people mutually accept; obeying these norms is an essential signal that someone is participating socially with respect to the rest of the population. For robots to be socially compatible with humans, it is crucial for robots to obey these social norms. In prior work, we demonstrated a Socially-Aware Navigation (SAN) planner, based on Pareto Concavity Elimination Transformation (PaCcET), in a hallway scenario, optimizing two objectives so …
Federal University of Santa Maria - UFSM（圣玛丽亚联邦大学（UFSM））；Universidade Federal do Rio Grande - FURG（里奥格兰德联邦大学（FURG））
Human-robot interaction (HRI) is essential to the widespread use of robots in daily life. Robots will eventually be able to carry out a variety of duties in human civilization through effective social interaction. Creating straightforward and understandable interfaces to engage with robots as they start to proliferate in the personal workspace is essential. Typically, interactions with simulated robots are displayed on screens. A more appealing alternative is virtual reality (VR), which gives visual cues more like those seen in the real world. In this study, we introduce Jubileo, a robotic ani…
OCAD University（安大略艺术设计大学）；University of Toronto Robotics Institute（多伦多大学机器人研究所）
Building trustworthy autonomous systems is challenging for many reasons beyond simply trying to engineer agents that 'always do the right thing.' There is a broader context that is often not considered within AI and HRI: that the problem of trustworthiness is inherently socio-technical and ultimately involves a broad set of complex human factors and multidimensional relationships that can arise between agents, humans, organizations, and even governments and legal institutions, each with their own understanding and definitions of trust. This complexity presents a significant barrier to the deve…
Classification of User Satisfaction in HRI with Social Signals in the Wild
TH Köln - University of Applied Sciences, Cologne Cobots Lab, Betzdorfer Str. 2, 50679, Germany（TH Köln应用科学大学，科隆Cobots实验室）；KI Park e.V. & FAU - Friedrich-Alexander University of Erlangen-Nuremberg（KI Park协会与弗赖堡-埃尔兰根-纽伦堡大学）
Gaze-Aware Task Progression Detection Framework for Human-Robot Interaction Using RGB Cameras
Department of Computer Science, Vrije Universiteit Amsterdam（范德比尔特大学阿姆斯特丹计算机科学系）；Department of Movement Sciences, Vrije Universiteit Amsterdam（范德比尔特大学阿姆斯特丹运动科学系）
L-CAS, University of Lincoln（林肯大学L-CAS（林肯大学林肯先进科学与工程中心））；University of Lincoln（林肯大学）；L-CAS（林肯先进科学与工程中心（L-CAS））
Continuously measuring the engagement of users with a robot in a Human-Robot Interaction (HRI) setting paves the way towards in-situ reinforcement learning, improve metrics of interaction quality, and can guide interaction design and behaviour optimisation. However, engagement is often considered very multi-faceted and difficult to capture in a workable and generic computational model that can serve as an overall measure of engagement. Building upon the intuitive ways humans successfully can assess situation for a degree of engagement when they see it, we propose a novel regression model (util…
University of Bristol（布里斯托大学）；University of the West of England（西英格兰大学）
The challenges of robotic software testing extend beyond conventional software testing. Valid, realistic and interesting tests need to be generated for multiple programs and hardware running concurrently, deployed into dynamic environments with people. We investigate the use of Belief-Desire-Intention (BDI) agents as models for test generation, in the domain of human-robot interaction (HRI) in simulations. These models provide rational agency, causality, and a reasoning mechanism for planning, which emulate both intelligent and adaptive robots, as well as smart testing environments directed by…
Örebro University（厄勒布鲁大学）；Robert Bosch GmbH（罗伯特·博世有限公司）；University of Skövde（舍夫德大学）
Robots are increasingly deployed in spaces shared with humans, including home settings and industrial environments. In these environments, the interaction between humans and robots (HRI) is crucial for safety, legibility, and efficiency. A key factor in HRI is trust, which modulates the acceptance of the system. Anthropomorphism has been shown to modulate trust development in a robot, but robots in industrial environments are not usually anthropomorphic. We designed a simple interaction in an industrial environment in which an anthropomorphic mock driver (ARMoD) robot simulates to drive an aut…
Faculty of Applied Sciences（应用科学学院）；School of Computing Science（计算科学学院）；FEMTO-ST Institute Centre national de la recherche scientifique (CNRS)（FEMTO-ST研究所，国家科学研究中心）；Centre national de la recherche scientifique (CNRS)（国家科学研究中心）
DiffCoTune: Differentiable Co-Tuning for Cross-domain Robot Control
Department of Aerospace and Mechanical Engineering, USC Viterbi School of Engineering（航空航天与机械工程系，USC维特比工程学院）；Department of Mechanical Science and Engineering, University of Illinois Urbana-Champaign（机械科学与工程系，伊利诺伊大学厄巴纳-香槟分校）
