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

Human-centred design methods : developing scenarios for robot assisted play informed by user panels and field trials

Original article can be found at: http://www.sciencedirect.com/ Copyright ElsevierThis article describes the user-centred development of play scenarios for robot assisted play, as part of the multidisciplinary IROMEC1 project that develops a novel robotic toy for children with special needs. The project investigates how robotic toys can become social mediators, encouraging children with special needs to discover a range of play styles, from solitary to collaborative play (with peers, carers/teachers, parents, etc.). This article explains the developmental process of constructing relevant play scenarios for children with different special needs. Results are presented from consultation with panel of experts (therapists, teachers, parents) who advised on the play needs for the various target user groups and who helped investigate how robotic toys could be used as a play tool to assist in the children’s development. Examples from experimental investigations are provided which have informed the development of scenarios throughout the design process. We conclude by pointing out the potential benefit of this work to a variety of research projects and applications involving human–robot interactions.Peer reviewe

Learning Dynamic Robot-to-Human Object Handover from Human Feedback

Object handover is a basic, but essential capability for robots interacting with humans in many applications, e.g., caring for the elderly and assisting workers in manufacturing workshops. It appears deceptively simple, as humans perform object handover almost flawlessly. The success of humans, however, belies the complexity of object handover as collaborative physical interaction between two agents with limited communication. This paper presents a learning algorithm for dynamic object handover, for example, when a robot hands over water bottles to marathon runners passing by the water station. We formulate the problem as contextual policy search, in which the robot learns object handover by interacting with the human. A key challenge here is to learn the latent reward of the handover task under noisy human feedback. Preliminary experiments show that the robot learns to hand over a water bottle naturally and that it adapts to the dynamics of human motion. One challenge for the future is to combine the model-free learning algorithm with a model-based planning approach and enable the robot to adapt over human preferences and object characteristics, such as shape, weight, and surface texture.Comment: Appears in the Proceedings of the International Symposium on Robotics Research (ISRR) 201

Setting the stage – embodied and spatial dimensions in emerging programming practices.

In the design of interactive systems, developers sometimes need to engage in various ways of physical performance in order to communicate ideas and to test out properties of the system to be realised. External resources such as sketches, as well as bodily action, often play important parts in such processes, and several methods and tools that explicitly address such aspects of interaction design have recently been developed. This combined with the growing range of pervasive, ubiquitous, and tangible technologies add up to a complex web of physicality within the practice of designing interactive systems. We illustrate this dimension of systems development through three cases which in different ways address the design of systems where embodied performance is important. The first case shows how building a physical sport simulator emphasises a shift in activity between programming and debugging. The second case shows a build-once run-once scenario, where the fine-tuning and control of the run-time activity gets turned into an act of in situ performance by the programmers. The third example illustrates the explorative and experiential nature of programming and debugging systems for specialised and autonomous interaction devices. This multitude in approaches in existing programming settings reveals an expanded perspective of what practices of interaction design consist of, emphasising the interlinking between design, programming, and performance with the system that is being developed

Explorations in engagement for humans and robots

This paper explores the concept of engagement, the process by which individuals in an interaction start, maintain and end their perceived connection to one another. The paper reports on one aspect of engagement among human interactors--the effect of tracking faces during an interaction. It also describes the architecture of a robot that can participate in conversational, collaborative interactions with engagement gestures. Finally, the paper reports on findings of experiments with human participants who interacted with a robot when it either performed or did not perform engagement gestures. Results of the human-robot studies indicate that people become engaged with robots: they direct their attention to the robot more often in interactions where engagement gestures are present, and they find interactions more appropriate when engagement gestures are present than when they are not.Comment: 31 pages, 5 figures, 3 table