Achieving Corresponding Effects on Multiple Robotic Platforms: Imitating in Context Using Different Effect Metrics

Original paper can be found at: www.aisb.org.uk/publications/proceedings/aisb05/3_Imitation_Final.pdfOne of the fundamental problems in imitation is the correspondence problem, how to map between the actions, states and effects of the model and imitator agents, when the embodiment of the agents is dissimilar. In our approach, the matching is according to different metrics and granularity. This paper presents JABBERWOCKY, a system that uses captured data from a human demonstrator to generate appropriate action commands, addressing the correspondence problem in imitation. Towards a characterization of the space of effect metrics, we are exploring absolute/relative angle and displacement aspects and focus on the overall arrangement and trajectory of manipulated objects. Using as an example a captured demonstration from a human, the system produces a correspondence solution given a selection of effect metrics and starting from dissimilar initial object positions, producing action commands that are then executed by two imitator target platforms (in simulation) to successfully imitate

Robot-Mediated Interviews with Children : What do potential users think?

Luke Wood, Hagen Lehmann, Kerstin Dautenhahn, Ben Robins, Austen Rayner, and Dag Syrdal, ‘Robot-Mediated Interviews with Children: What do potential users think?’, paper presented at the 50th Annual Convention of the Society for the Study of Artificial Intelligence and the Simulation of Behaviour, 1 April 2014 – 4 April 2014, London, UK.When police officers are conducting interviews with children, some of the disclosures can be quite shocking. This can make it difficult for an officer to maintain their composure without subtly indicating their shock to the child, which can in turn impede the information acquisition process. Using a robotic interviewer could eliminate this problem as the behaviours and expressions of the robot can be consciously controlled. To date research investigating the potential of Robot-Mediated Interviews has focused on establishing whether children will respond to robots in an interview scenario and if so how well. The results of these studies indicate that children will talk to a robot in an interview scenario in a similar way to which they talk to a human interviewer. However, in order to test if this approach would work in a real world setting, it is important to establish what the experts (e.g. specialist child interviewers) would require from the system. To determine the needs of the users we conducted a user panel with a group of potential real world users to gather their views of our current system and find out what they would require for the system to be useful to them. The user group we worked with consisted of specialist child protection police officers based in the UK. The findings from this panel suggest that a Robot-Mediated Interviewing system would need to be more flexible than our current system in order to respond to unpredictable situations and paths of investigation. This paper gives an insight into what real world users would need from a Robot-Mediated Interviewing system

Robot-mediated interviews : Does a robotic interviewer impact question difficulty and information recovery?

Luke Wood, Kerstin Dautenhahn, Hagen Lehmnn, Ben Robbins, Austen Rainer, and Dag Sverre Syrdal, 'Robot-Mediated Interviews: Does a Robotic Interviewer Impact Question Difficulty and Information Recovery?', Assistive Technology : From Research to Practice, proceedings of the AAATE 2013 Conference, 19 - 22 September 2013, Villamoura, Portugal, ISBN: 9781614993032 (print), ISBN: 9781614993049 (electronic), published by IOS Press. Available online at doi: 10.3233/978-1-61499-304-9-131Our previous research has shown that children respond to a robotic interviewer very similar compared to a human interviewer, pointing towards the prospect of using robot-mediated interviews in situations where human interviewers face certain challenges. This follow-up study investigated how 20 children (aged between 7 and 9) respond to questions of varying difficulty from a robotic interviewer compared to a human interviewer. Each child participated in two interviews, one with an adult and one with a humanoid robot called KASPAR, the main questions in these interviews focused on the theme of pets and animals. After each interview the children were asked to rate the difficulty of the questions and particular aspects of the experience. Measures include the behavioural coding of the children's behaviour during the interviews, the transcripts of what the children said and questionnaire data. The results from quantitative data analysis reveal that the children interacted with KASPAR in a very similar manner to how they interacted with the human interviewer, and provided both interviewers with similar information and amounts of information regardless of question difficulty

Integration of Action and Language Knowledge: A Roadmap for Developmental Robotics

“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.”This position paper proposes that the study of embodied cognitive agents, such as humanoid robots, can advance our understanding of the cognitive development of complex sensorimotor, linguistic, and social learning skills. This in turn will benefit the design of cognitive robots capable of learning to handle and manipulate objects and tools autonomously, to cooperate and communicate with other robots and humans, and to adapt their abilities to changing internal, environmental, and social conditions. Four key areas of research challenges are discussed, specifically for the issues related to the understanding of: 1) how agents learn and represent compositional actions; 2) how agents learn and represent compositional lexica; 3) the dynamics of social interaction and learning; and 4) how compositional action and language representations are integrated to bootstrap the cognitive system. The review of specific issues and progress in these areas is then translated into a practical roadmap based on a series of milestones. These milestones provide a possible set of cognitive robotics goals and test scenarios, thus acting as a research roadmap for future work on cognitive developmental robotics.Peer reviewe

A Pilot Study with a Novel Setup for Collaborative Play of the Humanoid Robot KASPAR with children with autism

This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.This article describes a pilot study in which a novel experimental setup, involving an autonomous humanoid robot, KASPAR, participating in a collaborative, dyadic video game, was implemented and tested with children with autism, all of whom had impairments in playing socially and communicating with others. The children alternated between playing the collaborative video game with a neurotypical adult and playing the same game with the humanoid robot, being exposed to each condition twice. The equipment and experimental setup were designed to observe whether the children would engage in more collaborative behaviours while playing the video game and interacting with the adult than performing the same activities with the humanoid robot. The article describes the development of the experimental setup and its first evaluation in a small-scale exploratory pilot study. The purpose of the study was to gain experience with the operational limits of the robot as well as the dyadic video game, to determine what changes should be made to the systems, and to gain experience with analyzing the data from this study in order to conduct a more extensive evaluation in the future. Based on our observations of the childrens’ experiences in playing the cooperative game, we determined that while the children enjoyed both playing the game and interacting with the robot, the game should be made simpler to play as well as more explicitly collaborative in its mechanics. Also, the robot should be more explicit in its speech as well as more structured in its interactions. Results show that the children found the activity to be more entertaining, appeared more engaged in playing, and displayed better collaborative behaviours with their partners (For the purposes of this article, ‘partner’ refers to the human/robotic agent which interacts with the children with autism. We are not using the term’s other meanings that refer to specific relationships or emotional involvement between two individuals.) in the second sessions of playing with human adults than during their first sessions. One way of explaining these findings is that the children’s intermediary play session with the humanoid robot impacted their subsequent play session with the human adult. However, another longer and more thorough study would have to be conducted in order to better re-interpret these findings. Furthermore, although the children with autism were more interested in and entertained by the robotic partner, the children showed more examples of collaborative play and cooperation while playing with the human adult.Peer reviewe

Interactional Structure Applied to the Identification and Generation of Visual Interactive Behavior: Robots that (Usually) Follow the Rules

Peer reviewe

Building Robota, a Mini-Humanoid Robot for the Rehabilitation of Children with Autism

The Robota project constructs a series of multiple degrees of freedom doll-shaped humanoid robots, whose physical features resemble those of a human baby. The Robota robots have been applied as assistive technologies in behavioral studies with low-functioning children with autism. These studies investigate the potential of using an imitator robot to assess children’s imitation ability and to teach children simple coordinated behaviors. In this paper, we review the recent technological developments that have made the Robota robots suitable for use with children with autism. We critically appraise the main outcomes of two sets of behavioral studies conducted with Robota and discuss how these results inform future development of the Robota robots and generally, robots for the rehabilitation of children with complex developmental disabilities

Mean Field Fluid Behavior of the Gaussian Core Model

We show that the Gaussian core model of particles interacting via a penetrable repulsive Gaussian potential, first considered by Stillinger (J. Chem. Phys. 65, 3968 (1976)), behaves like a weakly correlated ``mean field fluid'' over a surprisingly wide density and temperature range. In the bulk the structure of the fluid phase is accurately described by the random phase approximation for the direct correlation function, and by the more sophisticated HNC integral equation. The resulting pressure deviates very little from a simple, mean-field like, quadratic form in the density, while the low density virial expansion turns out to have an extremely small radius of convergence. Density profiles near a hard wall are also very accurately described by the corresponding mean-field free-energy functional. The binary version of the model exhibits a spinodal instability against de-mixing at high densities. Possible implications for semi-dilute polymer solutions are discussed.Comment: 13 pages, 2 columns, ReVTeX epsfig,multicol,amssym, 15 figures; submitted to Phys. Rev. E (change: important reference added