Modern robots are stepping away from monolithic entities built using ad-hoc sensors and actuators, due to new technologies and communication paradigms, such as the Internet of Things (IoT) and the Robotic Operating System (ROS). Using such paradigms, robots can be built by acquiring heterogeneous standard devices and putting them in communication with each other. This approach brings high degrees of modularity, but it also yields uncertainty of providing cybersecurity assurances, and guarantees on the integrity of the embodiment. In this paper, we first illustrate how cyberattacks on different devices can have radically different consequences on the robot's ability to complete its tasks and preserve its embodiment. We also claim that modern robots should have self-awareness for what it concerns such aspects, and formulate the different characteristics that robots should integrate for doing so. Then, we show that achieving these propositions requires that robots possess at least three properties that conceptually link devices and tasks. Last, we reflect on how these three properties could be achieved in a larger conceptual framework.

Since it has often been claimed by academics that reconfiguration is essential, many approaches to reconfiguration, especially of robotic systems, have been developed. Accordingly, the literature on robotics is rich in techniques for reconfiguring robotic systems. However, when talking to researchers in the domain, there seems to be no common understanding of what exactly reconfiguration is and how it relates to other concepts such as adaptation. Beyond this academic perspective, robotics frameworks provide mechanisms for dynamically loading and unloading parts of robotics applications. While we have a fuzzy picture of the state-of-the-art in robotic reconfiguration from an academic perspective, we lack a picture of the state-of-practice from a practitioner perspective. To fill this gap, we survey the literature on reconfiguration in robotic systems by identifying and analyzing 98 relevant papers, review how four major robotics frameworks support reconfiguration, and finally investigate the realization of reconfiguration in 48 robotics applications. When comparing the state-of-the-art with the state-of-practice, we observed a significant discrepancy between them, in particular, the scientific community focuses on complex structural reconfiguration, while in practice only parameter reconfiguration is widely used. Based on our observations, we discuss possible reasons for this discrepancy and conclude with a takeaway message for academics and practitioners interested in robotics.

Writing software for robotic platforms can be arduous, time-consuming, and error-prone. In recent years, the number of research groups working in robotics has grown exponentially, each group having platforms with peculiar characteristics. The choice of morphology, actuation systems, and sensing technology is virtually unlimited, and code reuse is fundamental to getting new robots up and running in the shortest possible time. In addition, it is pervasive for researchers willing to test new ideas in simulation without wasting time in coding, for instance, using high-level languages for rapid code prototyping. To pursue these goals, in the past years several robotics frameworks have been designed for teaching or for controlling specific platforms, e.g., OpenRAVE [1], Drake [2] and SL [3].

Neurological studies (Rizzolatti and Craighero 2004) have shown that activity in the premotor In the United States, the rapid increase in the population of cortex may represent the integration of auditory information children with autism spectrum disorder (ASD) has revealed with temporally organized motor action during rhythmic the deficiency in the realm of therapeutic accessibility for cuing. Based on this theory, researchers have shown children with ASD in the domain of emotion and social that RAS can produce significant improvements in physical interaction. There have been a number of approaches including activities (Pacchetti et al. 2000). Given that music has several robotic therapeutic systems (Feil-Seifer and shown such a long history of therapeutic effects on psychological Mataric 2008; Scassellati, Admoni, and Mataric 2012) displaying (Siedliecki and Good 2006) and physical problems many intriguing strategies and meaningful results.