Developing social action capabilities in a humanoid robot using an interaction history architecture

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.” DOI: 10.1109/ICHR.2008.4756013We present experimental results for the humanoid robot Kaspar2 engaging in a simple “peekaboo” interaction game with a human partner. The robot develops the capability to engage in the game by using its history of interactions coupled with audio and visual feedback from the interaction partner to continually generate increasingly appropriate behaviour. The robot also uses facial expressions to feedback its level of reward to the partner. The results support the hypothesis that reinforcement of time-extended experiences through interaction allows a robot to act appropriately in an interaction

Robot Self-Characterisation of Experience Using Trajectories in Sensory-Motor Phase Space

Peer reviewe

Exploring the Design Space of Robot Appearance and Behavior in an Attention-Seeking Living Room Scenario for a Robot Companion

This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder.---- Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. --DOI : 10.1109/ALIFE.2007.36781

An empirical framework for human-robot proxemics

The work described in this paper was conducted within the EU Integrated Projects COGNIRON ("The Cognitive Robot Companion") and LIREC (LIving with Robots and intEractive Companions) and was funded by the European Commission under contract numbers FP6- 002020 and FP7-215554.An empirical framework for Human-Robot (HR) proxemics is proposed which shows how the measurement and control of interpersonal distances between a human and a robot can be potentially used by the robot to interpret, predict and manipulate proxemic behaviour for Human-Robot Interactions (HRIs). The proxemic framework provides for incorporation of inter-factor effects, and can be extended to incorporate new factors, updated values and results. The framework is critically discussed and future work proposed

Close encounters : spatial distances between people and a robot of mechanistic appearance

Peer reviewe

Statistical Performance Analysis of an Ant-Colony Optimisation Application in S-NET

Kenneth MacKenzie, Philip K. F. Hölzenspies, Kevin Hammond, Raimund Kirner, Vu Thien Nga Nguyen, Iraneus te Boekhorst, Clemens Grelck, Raphael Poss, Merijn Verstraaten, 'Statistical Performance Analysis of an Ant-Colony Optimisation Application in S-NET'. Paper presented at the 2nd Workshop on Feedback-Directed Compiler Optimization for Multi-Core Architectures. Berlin, Germany, 12 January 2013.We consider an ant-colony optimsation problem implemented on a multicore system as a collection of asynchronous stream- processing components under the control of the S-NET coordina- tion language. Statistical analysis and visualisation techniques are used to study the behaviour of the application, and this enables us to discover and correct problems in both the application program and the run-time system underlying S-NET

The COVID-19 outbreak increases maternal stress during pregnancy, but not the risk for postpartum depression

The COVID-19 pandemic affects society and may especially have an impact on mental health of vulnerable groups, such as perinatal women. This prospective cohort study of 669 participating women in the Netherlands compared perinatal symptoms of depression and stress during and before the pandemic. After a pilot in 2018, recruitment started on 7 January 2019. Up until 1 March 2020 (before the pandemic), 401 women completed questionnaires during pregnancy, of whom 250 also completed postpartum assessment. During the pandemic, 268 women filled out at least one questionnaire during pregnancy and 59 postpartum (1 March-14 May 2020). Pregnancy-specific stress increased significantly in women during the pandemic. We found no increase in depressive symptoms during pregnancy nor an increase in incidence of high levels of postpartum depressive symptoms during the pandemic. Clinicians should be aware of the potential for increased stress in pregnant women during the pandemic

Robotic assistants in therapy and education of children with autism: Can a small humanoid robot help encourage social interaction skills?

This article presents a longitudinal study with four children with autism, who were exposed to a humanoid robot over a period of several months. The longitudinal approach allowed the children time to explore the space of robot– human, as well as human–human interaction. Based on the video material documenting the interactions, a quantitative and qualitative analysis was conducted. The quantitative analysis showed an increase in duration of pre-defined behaviours towards the later trials. A qualitative analysis of the video data, observing the children’s activities in their interactional context, revealed further aspects of social interaction skills (imitation, turn-taking and role- switch) and communicative competence that the children showed. The results clearly demonstrate the need for, and benefits of, long-term studies in order to reveal the full potential of robots in the therapy and education of children with autism