Dance Teaching by a Robot: Combining Cognitive and Physical Human-Robot Interaction for Supporting the Skill Learning Process

This letter presents a physical human-robot interaction scenario in which a robot guides and performs the role of a teacher within a defined dance training framework. A combined cognitive and physical feedback of performance is proposed for assisting the skill learning process. Direct contact cooperation has been designed through an adaptive impedance-based controller that adjusts according to the partner's performance in the task. In measuring performance, a scoring system has been designed using the concept of progressive teaching (PT). The system adjusts the difficulty based on the user's number of practices and performance history. Using the proposed method and a baseline constant controller, comparative experiments have shown that the PT presents better performance in the initial stage of skill learning. An analysis of the subjects' perception of comfort, peace of mind, and robot performance have shown a significant difference at the p < .01 level, favoring the PT algorithm.Comment: Presented at IEEE International Conference on Robotics and Automation ICRA-201

Towards a framework to make robots learn to dance

A key motive of human-robot interaction is to make robots and humans interact through different aspects of the real world. As robots become more and more realistic in appearance, so has the desire for them to exhibit complex behaviours. A growing area of interest in terms of complex behaviour is robot dancing. Dance is an entertaining activity that is enjoyed either by being the performer or the spectator. Each dance contain fundamental features that make-up a dance. It is the curiosity for some researchers to model such an activity for robots to perform in human social environments. From current research, most dancing robots are pre-programmed with dance motions and few have the ability to generate their own dance or alter their movements according to human responses while dancing. This thesis explores the question Can a robot learn to dance? . A dancing framework is proposed to address this question. The Sarsa algorithm and the Softmax algorithm from traditional reinforcement learning form part of the dancing framework to enable a virtual robot learn and adapt to appropriate dance behaviours. The robot follows a progressive approach, utilising the knowledge obtained at each stage of its development to improve the dances that it generates. The proposed framework addresses three stages of development of a robot s dance: learning ability; creative ability of dance motions, and adaptive ability to human preferences. Learning ability is the ability to make a robot gradually perform the desired dance behaviours. Creative ability is the idea of the robot generating its own dance motions, and structuring them into a dance. Adaptive ability is where the robot changes its dance in response to human feedback. A number of experiments have been conducted to explore these challenges, and verified that the quality of the robot dance can be improved through each stage of the robot s development

From rituals to magic: Interactive art and HCI of the past, present, and future

The connection between art and technology is much tighter than is commonly recognized. The emergence of aesthetic computing in the early 2000s has brought renewed focus on this relationship. In this article, we articulate how art and Human–Computer Interaction (HCI) are compatible with each other and actually essential to advance each other in this era, by briefly addressing interconnected components in both areas—interaction, creativity, embodiment, affect, and presence. After briefly introducing the history of interactive art, we discuss how art and HCI can contribute to one another by illustrating contemporary examples of art in immersive environments, robotic art, and machine intelligence in art. Then, we identify challenges and opportunities for collaborative efforts between art and HCI. Finally, we reiterate important implications and pose future directions. This article is intended as a catalyst to facilitate discussions on the mutual benefits of working together in the art and HCI communities. It also aims to provide artists and researchers in this domain with suggestions about where to go next

16th Sound and Music Computing Conference SMC 2019 (28&#8211;31 May 2019, Malaga, Spain)

The 16th Sound and Music Computing Conference (SMC 2019) took place in Malaga, Spain, 28-31 May 2019 and it was organized by the Application of Information and Communication Technologies Research group (ATIC) of the University of Malaga (UMA). The SMC 2019 associated Summer School took place 25-28 May 2019. The First International Day of Women in Inclusive Engineering, Sound and Music Computing Research (WiSMC 2019) took place on 28 May 2019. The SMC 2019 TOPICS OF INTEREST included a wide selection of topics related to acoustics, psychoacoustics, music, technology for music, audio analysis, musicology, sonification, music games, machine learning, serious games, immersive audio, sound synthesis, etc

Advances in Human-Robot Interaction

Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers