Robotics and Design: An Interdisciplinary Crash Course

The authors designed and ran a crash course on emotional robotics involving students from both the Information Engineering School and the Design School of Politecnico di Milano , Milan, Italy. The course consisted of two intensive days of short introductory lessons and lab activity, done in interdisciplinary groups and supported by a well-equipped prototyping and modeling lab. People from very different backgrounds had to work efficiently together, going from problem setting through the demonstration of the physical implementation of an object able to show four different emotional states. Both teacher evaluation and questionnaire-based feedback from the students show that it was successful and useful to set up this type of intensive experience in which students share their abilities to achieve a common goal. Key aspects for the success of the course were the short time the students had to reach a well-defined, yet general, goal, the students' ability to find efficient ways of cooperating and sharing their competences, students' motivation to arrive at a working prototype, and the strong support from teachers and lab personnel

Studying People's Emotional Responses to Robot's Movements

With a deeper interaction between robots and humans, the emotional rapport between the two is becoming ever more important. The interpretation of emotion expressed by robots has been widely studied with humanoids and animal-like robots, which try to mimic biological beings similar to those people is used to interact with. Considering the uncanny valley issue and the practical and theoretical questions related to implement bio-inspired robots, it may be argued whether also object-like robots can express emotions so that people can satisfactorily interact with robots that can have functional shapes, not necessarily bio-insipired. This paper presents some study cases done to identify body features that allow emotion projection from an object-like robot body. The study was done in two phases: a pilot experiment, and a formal trial. The results show that is possible to project different emotions by exploiting angular and linear velocity of the robot

Physically Interactive Robogames: Definition and Design Guidelines

There is evidence that people expects to be able to play games with autonomous robots, so that robogames could be one of the next killer ap- plications for Robotics. Physically Interactive RoboGames (PIRG) is a new application field where autonomous robots are involved in games requiring physical interaction with people. Since research in this field is moving its first steps, definitions and design guidelines are still largely missing. n this paper, a definition for PIRG is proposed, together with guidelines for their design. Physically Interactive, Competitive RoboGames (PICoRG) are also introduced. They are a particular kind of PIRG where human players are involved in a challenging, highly interactive and competitive game activity with autonomous robots. The development process of a PICoRG, Jedi Trainer , is presented to show a practical application of the proposed guidelines. The game has been successfully played in different unstructured environments, by general public; feedback is reported and analysed

Head Impact Severity Measures for Small Social Robots Thrown During Meltdown in Autism

Social robots have gained a lot of attention recently as they have been reported to be effective in supporting therapeutic services for children with autism. However, children with autism may exhibit a multitude of challenging behaviors that could be harmful to themselves and to others around them. Furthermore, social robots are meant to be companions and to elicit certain social behaviors. Hence, the presence of a social robot during the occurrence of challenging behaviors might increase any potential harm. In this paper, we identified harmful scenarios that might emanate between a child and a social robot due to the manifestation of challenging behaviors. We then quantified the harm levels based on severity indices for one of the challenging behaviors (i.e. throwing of objects). Our results showed that the overall harm levels based on the selected severity indices are relatively low compared to their respective thresholds. However, our investigation of harm due to throwing of a small social robot to the head revealed that it could potentially cause tissue injuries, subconcussive or even concussive events in extreme cases. The existence of such behaviors must be accounted for and considered when developing interactive social robots to be deployed for children with autism.The work is supported by a research grant from Qatar University under the grant No. QUST-1-CENG-2018-7Scopu

Data on the impact of objects with different shapes, masses, and impact velocities on a dummy head

In this article, a data generated from impacts of objects with different shapes, masses, and impact velocities on a developed dummy head. The mass considered was in the range of 0.3-0.5 kg while the shapes considered were cube, wedge, and cylinder. The impact velocities levels were in the range of 1-3 m/s. A total of 144 experiments were conducted and the corresponding videos and raw data were analyzed for impact velocity, peak head linear acceleration, 3 ms criterion, and the Head Injury Criterion (HIC). This dataset includes the raw acceleration data and a summary of the overall processed data. The data is available on Harvard Dataverse: https://doi.org/10.7910/DVN/AVC8GG.The work is supported by a research grant from Qatar University under the Grant no. QUST-1-CENG-2018-7 .Scopu

Pain and self-preservation in autonomous robots: From neurobiological models to psychiatric disease

The use of biologically realistic (brain-like) control systems in autonomous robots offers two potential benefits. For neuroscience, it may provide important insights into normal and abnormal control and decision-making in the brain, by testing whether the computational learning and decision rules proposed on the basis of simple laboratory experiments lead to effective and coherent behaviour in complex environments. For robotics, it may offer new insights into control system designs, for example in the context of threat avoidance and self-preservation. In the brain, learning and decision-making for rewards and punishments (such as pain) are thought to involve integrated systems for innate (Pavlovian) responding, habit-based learning, and goal-directed learning, and these systems have been shown to be well-described by RL models. Here, we simulated this 3-system control hierarchy (in which the innate system is derived from an evolutionary learning model), and show that it reliably achieves successful performance in a dynamic predator-avoidance task. Furthermore, we show situations in which a 3-system architecture provides clear advantages over single or dual system architectures. Finally, we show that simulating a computational model of obsessive compulsive disorder, an example of a disease thought to involve a specific deficit in the integration of habit-based and goal-directed systems, can reproduce the results of human clinical experiments. The results illustrate how robotics can provide a valuable platform to test the validity and utility of computational models of human behaviour, in both health and disease. They also illustrate how bio-inspired control systems might usefully inform self-preservative behaviour in autonomous robots, both in normal and malfunctioning situations

Omni-directional catadioptric vision for soccer robots

This paper describes the design of a multi-part mirror catadioptric vision system and its use for self-localization and detection of relevant objects in soccer robots. The mirror and associated algorithms have been used in robots participating in the middle-size league of RoboCup — The World Cup of Soccer Robots.This work was supported by grant PRAXIS XXI BM/21091/99 of the Portuguese Foundation for Science and Technolog

A bird's eye view on reinforcement learning approaches for power management in WSNs

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The potential of robotics for the development and wellbeing of children with disabilities as we see it.

BACKGROUND: Rapid technological development has been opening new possibilities for children with disabilities. In particular, robots can enable and create new opportunities in therapy, rehabilitation, education, or leisure. OBJECTIVE: The aim of this article is to share experiences, challenges and learned lessons by the authors, all of them with experience conducting research in the field of robotics for children with disabilities, and to propose future directions for research and development. METHODS: The article is the result of several consensus meetings to establish future research priorities in this field. RESULTS: Robots have a huge potential to support children with disabilities: they can play the role of a play buddy, of a mediator when interacting with other children or adults, they can promote social interaction, and transfer children from the role of a spectator of the surrounding world to the role of an active participant. To fulfill their potential, robots have to be “smart”, stable and reliable, easy to use and program, and give the just-right amount of support adapted to the needs of the child. Interdisciplinary collaboration combined with user centered design is necessary to make robotic applications successful. Furthermore, real-life contexts to test and implement robotic interventions are essential to refine them according to real needs. CONCLUSIONS: This article outlines a research agenda for the future of robotics in childcare and supports the establishment of R4C – Robots for Children, a network of experts aimed at sharing ideas, promoting innovative research, and developing good practices on the use of robots for children with disabilities

The potential of robotics for the development and wellbeing of children with disabilities as we see it

BACKGROUND: Rapid technological development has been opening new possibilities for children with disabilities. In particular, robots can enable and create new opportunities in therapy, rehabilitation, education, or leisure. OBJECTIVE: The aim of this article is to share experiences, challenges and learned lessons by the authors, all of them with experience conducting research in the field of robotics for children with disabilities, and to propose future directions for research and development. METHODS: The article is the result of several consensus meetings to establish future research priorities in this field. RESULTS: Robots have a huge potential to support children with disabilities: they can play the role of a play buddy, of a mediator when interacting with other children or adults, they can promote social interaction, and transfer children from the role of a spectator of the surrounding world to the role of an active participant. To fulfill their potential, robots have to be 'smart', stable and reliable, easy to use and program, and give the just-right amount of support adapted to the needs of the child. Interdisciplinary collaboration combined with user centered design is necessary to make robotic applications successful. Furthermore, real-life contexts to test and implement robotic interventions are essential to refine them according to real needs. CONCLUSIONS: This article outlines a research agenda for the future of robotics in childcare and supports the establishment of R4C - Robots for Children, a network of experts aimed at sharing ideas, promoting innovative research, and developing good practices on the use of robots for children with disabilities