Evaluation of Passing Distance for Social Robots

(c) 2006 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works.The 15th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN06); Hatfield, UK; September 6-8, 2006.Digital Object Identifier : 10.1109/ROMAN.2006.314436Casual encounters with mobile robots for nonexperts can be a challenge due to lack of an interaction model. The present work is based on the rules from proxemics which are used to design a passing strategy. In narrow corridors the lateral distance of passage is a key parameter to consider. An implemented system has been used in a small study to verify the basic parametric design for such a system. In total 10 subjects evaluated variations in proxemics for encounters with a robot in a corridor setting. The user feedback indicates that entering the intimate sphere of people is less comfortable, however a too significant avoidance is also considered unnecessary. Adequate signaling of avoidance is a behaviour that must be carefully tuned

Pedestrian Models for Robot Motion

We discuss the development of a robot system able to replicate human group motion and show how a pedestrian model may be converted to a robot control system in order to achieve this goal

Social Navigation in a Cognitive Architecture Using Dynamic Proxemic Zones

[EN] Robots have begun to populate the everyday environments of human beings. These social robots must perform their tasks without disturbing the people with whom they share their environment. This paper proposes a navigation algorithm for robots that is acceptable to people. Robots will detect the personal areas of humans, to carry out their tasks, generating navigation routes that have less impact on human activities. The main novelty of this work is that the robot will perceive the moods of people to adjust the size of proxemic areas. This work will contribute to making the presence of robots in human-populated environments more acceptable. As a result, we have integrated this approach into a cognitive architecture designed to perform tasks in human-populated environments. The paper provides quantitative experimental results in two scenarios: controlled, including social navigation metrics in comparison with a traditional navigation method, and non-controlled, in robotic competitions where different studies of social robotics are measured.SIGobierno de España (TIN2016-76515-R grant for the COMBAHO project, supported with Feder funds )Comunidad de Madrid (RoboCity2030-DIH-CM (S2018/NMT-4331)

Towards a Methodology for Longitudinal Evaluation of Social Robotic Telepresence for Elderly

This paper describes a methodology for performing longitudinal evaluations when a social robotic telepresence system is deployed in realistic environments. This work is the core of an Ambient Assisted Living Project called ExCITE, Enabling Social Interaction Through Telepresence. The ExCITE project is geared towards an elderly audience and has as aim to increase social interaction among elderly, their family and healthcare services by using robotic telepresence. The robotic system used in the project is called the Giraff robot and over a three year period, prototypes of this platform are deployed at a number of test-sites in different European countries where user feedback is collected and feedback into the refinement of the prototype. In this paper, we discuss the methodology of ExCITE in particular relation to other methodologies for longitudinal evaluation. The paper also provides a discussion of the possible pitfalls and risks in performing longitudinal studies of this nature particularly as they relate to social robotic telepresence technologies

Impact of decision-making system in social navigation

[EN] Facing human activity-aware navigation with a cognitive architecture raises several difficulties integrating the components and orchestrating behaviors and skills to perform social tasks. In a real-world scenario, the navigation system should not only consider individuals like obstacles. It is necessary to offer particular and dynamic people representation to enhance the HRI experience. The robot’s behaviors must be modified by humans, directly or indirectly. In this paper, we integrate our human representation framework in a cognitive architecture to allow that people who interact with the robot could modify its behavior, not only with the interaction but also with their culture or the social context. The human representation framework represents and distributes the proxemic zones’ information in a standard way, through a cost map. We have evaluated the influence of the decision-making system in human-aware navigation and how a local planner may be decisive in this navigation. The material developed during this research can be found in a public repository (https://github.com/IntelligentRoboticsLabs/social_navigation2_WAF) and instructions to facilitate the reproducibility of the results.S

移動ロボットのための顔インタフェースを利用した動作予告に関する研究

筑波大学修士(情報学)学位論文・平成31年3月25日授与(41295号

A bellboy robot: Study of the effects of robot behaviour on user engagement and comfort

Producción CientíficaThis paper provides the results of various trial experiments in a hotel environment carried out using Sacarino, an interactive bellboy robot. We analysed which aspects of the robot design and behaviour are relevant in terms of user engagement and comfort when interacting with our social robot. The experiments carried out focused on the influence over proxemics, duration and effectiveness of the interaction taking into account three dichotomous factors related with the robot design and behaviour: robot embodiment (with/without robotic body), status of the robot (awake/asleep) and who starts communication (robot/user). Results show that users tend to maintain a personal distance when interacting with an embodied robot and that embodiment engages users in maintaining longer interactions. On the other hand, including a greeting model in a robot is useful in terms of engaging users to maintain longer interactions, and that an active-looking robot is more attractive to the participants, producing longer interactions than in the case of a passive-looking robot.Junta de Castilla y León (Programa de apoyo a proyectos de investigación-Ref. VA036U14)Junta de Castilla y León (Programa de apoyo a proyectos de investigación-Ref. VA013A12-2)Ministerio de Economía, Industria y Competitividad (Grant DPI2014-56500-R

Making Appearances:How Robots Should Approach People

To prepare for a future in which robots are more commonplace, it is important to know what robot behaviors people find socially normative. Previous work suggests that for robots to be accepted by people, the robot should adhere to the prevalent social norms, such as those related to approaching people. However, we do not expect that socially normative approach behaviors for robots can be translated on a one-on-one basis from people to robots, because currently robots have unique and different features to humans, including (but not limited to) wheels, sounds, and shapes. The two studies presented in this article go beyond the state-of-the-art and focus on socially normative approach behaviors for robots. In the first study, we compared people's responses to violations of personal space done by robots compared to people. In the second study, we explored what features (sound, size, speed) of a robot approaching people have an effect on acceptance. Findings indicate that people are more lenient toward violations of a social norm by a robot as compared to a person. Also, we found that robots can use their unique features to mitigate the negative effects of norm violations by communicating intent.</p

Approaching a person in a socially acceptable manner using expanding random trees

In real world scenarios for mobile robots, socially acceptable navigation is a key component to interact naturally with other persons. On the one hand this enables a robot to behave more human-like, and on the other hand it increases the acceptance of the user towards the robot as an interaction partner. As part of this research field, we present in this paper a strategy of approaching a person in a socially acceptable manner. Therefore, we use the theory of ”personal space” and present a method of modeling this space to enable a mobile robot to approach a person from the front. We use a standard Dynamic Window Approach to control the robot motion and, since the personal space model could not be used directly, a graph planner in configuration space, to plan an optimal path by expanding the graph with the use of the DWA’s update rule. Additionally, we give a proof of concept with first preliminary experiments

A Bayesian hierarchy for robust gaze estimation in human–robot interaction

In this text, we present a probabilistic solution for robust gaze estimation in the context of human–robot interaction. Gaze estimation, in the sense of continuously assessing gaze direction of an interlocutor so as to determine his/her focus of visual attention, is important in several important computer vision applications, such as the development of non-intrusive gaze-tracking equipment for psychophysical experiments in neuroscience, specialised telecommunication devices, video surveillance, human–computer interfaces (HCI) and artificial cognitive systems for human–robot interaction (HRI), our application of interest. We have developed a robust solution based on a probabilistic approach that inherently deals with the uncertainty of sensor models, but also and in particular with uncertainty arising from distance, incomplete data and scene dynamics. This solution comprises a hierarchical formulation in the form of a mixture model that loosely follows how geometrical cues provided by facial features are believed to be used by the human perceptual system for gaze estimation. A quantitative analysis of the proposed framework's performance was undertaken through a thorough set of experimental sessions. Results show that the framework performs according to the difficult requirements of HRI applications, namely by exhibiting correctness, robustness and adaptiveness