Hidden Markov Model Deep Learning Architecture for Virtual Reality Assessment to Compute Human–Machine Interaction-Based Optimization Model

Virtual Reality (VR) is a technology that immerses users in a simulated, computer-generated environment. It creates a sense of presence, allowing individuals to interact with and experience virtual worlds. Human-Machine Interaction (HMI) refers to the communication and interaction between humans and machines. Optimization plays a crucial role in Virtual Reality (VR) and Human-Machine Interaction (HMI) to enhance the overall user experience and system performance. This paper proposed an architecture of the Hidden Markov Model with  Grey Relational Analysis (GRA) integrated with Salp Swarm Algorithm (SSA) for the automated Human-Machine Interaction. The proposed architecture is stated as a Hidden Markov model Grey Relational Salp Swarm (HMM_ GRSS). The proposed HMM_GRSS model estimates the feature vector of the variables in the virtual reality platform and compute the feature spaces. The HMM_GRSS architecture aims to estimate the feature vector of variables within the VR platform and compute the feature spaces. Hidden Markov Models are used to model the temporal behavior and dynamics of the system, allowing for predictions and understanding of the interactions. Grey Relational Analysis is employed to evaluate the relationship and relevance between variables, aiding in feature selection and optimization. The SSA helps optimize the feature spaces by simulating the collective behavior of salp swarms, improving the efficiency and effectiveness of the HMI system. The proposed HMM_GRSS architecture aims to enhance the automated HMI process in a VR platform, allowing for improved interaction and communication between humans and machines. Simulation analysis provides a significant outcome for the proposed HMM_GRSS model for the estimation Human-Machine Interaction

Choreographic and Somatic Approaches for the Development of Expressive Robotic Systems

As robotic systems are moved out of factory work cells into human-facing environments questions of choreography become central to their design, placement, and application. With a human viewer or counterpart present, a system will automatically be interpreted within context, style of movement, and form factor by human beings as animate elements of their environment. The interpretation by this human counterpart is critical to the success of the system's integration: knobs on the system need to make sense to a human counterpart; an artificial agent should have a way of notifying a human counterpart of a change in system state, possibly through motion profiles; and the motion of a human counterpart may have important contextual clues for task completion. Thus, professional choreographers, dance practitioners, and movement analysts are critical to research in robotics. They have design methods for movement that align with human audience perception, can identify simplified features of movement for human-robot interaction goals, and have detailed knowledge of the capacity of human movement. This article provides approaches employed by one research lab, specific impacts on technical and artistic projects within, and principles that may guide future such work. The background section reports on choreography, somatic perspectives, improvisation, the Laban/Bartenieff Movement System, and robotics. From this context methods including embodied exercises, writing prompts, and community building activities have been developed to facilitate interdisciplinary research. The results of this work is presented as an overview of a smattering of projects in areas like high-level motion planning, software development for rapid prototyping of movement, artistic output, and user studies that help understand how people interpret movement. Finally, guiding principles for other groups to adopt are posited.Comment: Under review at MDPI Arts Special Issue "The Machine as Artist (for the 21st Century)" http://www.mdpi.com/journal/arts/special_issues/Machine_Artis

Design for Child-Robot Play The implications of Design Research within the field of Human-Robot Interaction studies for Children

This thesis investigates the intersections of three disciplines, that are Design Research, Human-Robot Interaction studies, and Child Studies. In particular, this doctoral research is focused on two research questions, namely, what is (or might be) the role of design research in HRI? And, how to design acceptable and desirable child-robot play applications? The first chapter introduces an overview of the mutual interest between robotics and design that is at the basis of the research. On the one hand, the interest of design toward robotics is documented through some exemplary projects from artists and designers that speculate on the human-robot coexistence condition. Vice versa, the robotics interest toward design is documented by referring to some tracks of robotic conferences, scienti c workshops and robotics journals which focused on the design-robotics relationship. Finally, a brief description of the background conditions that characterized this doctoral research are introduced, such as the fact of being a research founded by a company. The second chapter provides an overview of the state of the art of the intersections between three multidisciplinary disciplines. First, a de nition of Design Research is provided, together with its main trends and open issues. Then, the review focuses on the contribution of Design Research to the HRI eld, which can be summed up in actions focused on three aspects: artefacts, stakeholders, and contexts. This is followed by a focus on the role of Design Research within the context of children studies, in which it is possible to identify two main design-child relationships: design as a method for developing children’s learning experiences; and children as part of the design process for developing novel interactive systems. The third chapter introduces the Research through Design (RtD) approach and its relevance in conducting design research in HRI. The proposed methodology, based on this approach, is particularly characterized by the presence of design explorations as study methods. These, in turn, are developed through a common project’s methodology, also reported in this chapter. The fourth chapter is dedicated to the analysis of the scenario in which the child-robot interaction takes place. This was aimed at understanding what is edutainment robotics for children, its common features, how it relates to existing children play types, and where the interaction takes place. The chapter provides also a focus on the relationship between children and technology on a more general level, through which two themes and relative design opportunities were identi ed: physically active play and objects-to-think-with. These were respectively addressed in the two design explorations presented in this thesis: Phygital Play and Shybo. The Phygital Play project consists of an exploration of natural interaction modalities with robots, through mixed-reality, for fostering children’s active behaviours. To this end, a game platform was developed for allowing children to play with or against a robot, through body movement. Shybo, instead, is a low-anthropomorphic robot for playful learning activities with children that can be carried out in educational contexts. The robot, which reacts to properties of the physical environment, is designed to support different kinds of experiences. Then, the chapter eight is dedicated to the research outcomes, that were de ned through a process of reflection. The contribution of the research was analysed and documented by focusing on three main levels, namely: artefact, knowledge and theory. The artefact level corresponds to the situated implementations developed through the projects. The knowledge level consists of a set of actionable principles, emerged from the results and lessons learned from the projects. At the theory level, a theoretical framework was proposed with the aim of informing the future design of child- robot play applications. Thelastchapterprovidesa naloverviewofthe doctoral research, a series of limitations regarding the research, its process and its outcomes, and some indications for future research

Recent Advancements in Augmented Reality for Robotic Applications: A Survey

Robots are expanding from industrial applications to daily life, in areas such as medical robotics, rehabilitative robotics, social robotics, and mobile/aerial robotics systems. In recent years, augmented reality (AR) has been integrated into many robotic applications, including medical, industrial, human–robot interactions, and collaboration scenarios. In this work, AR for both medical and industrial robot applications is reviewed and summarized. For medical robot applications, we investigated the integration of AR in (1) preoperative and surgical task planning; (2) image-guided robotic surgery; (3) surgical training and simulation; and (4) telesurgery. AR for industrial scenarios is reviewed in (1) human–robot interactions and collaborations; (2) path planning and task allocation; (3) training and simulation; and (4) teleoperation control/assistance. In addition, the limitations and challenges are discussed. Overall, this article serves as a valuable resource for working in the field of AR and robotic research, offering insights into the recent state of the art and prospects for improvement

Integrating Human Inputs with Autonomous Behaviors on an Intelligent Wheelchair Platform

Researchers have developed and assessed a computer-controlled wheelchair called the Smart Chair. A shared control framework has different levels of autonomy, allowing the human operator complete control of the chair at each level while ensuring the user\u27s safety. The semiautonomous system incorporates deliberative motion plans or controllers, reactive behaviors, and human user inputs. At every instant in time, control inputs from three sources are integrated continuously to provide a safe trajectory to the destination. Experiments with 50 participants demonstrate quantitatively and qualitatively the benefits of human-robot augmentation in three modes of operation: manual, autonomous, and semiautonomous. This article is part of a special issue on Interacting with Autonomy

A framework for digitisation of manual manufacturing task knowledge using gaming interface technology

Intense market competition and the global skill supply crunch are hurting the manufacturing industry, which is heavily dependent on skilled labour. Companies must look for innovative ways to acquire manufacturing skills from their experts and transfer them to novices and eventually to machines to remain competitive. There is a lack of systematic processes in the manufacturing industry and research for cost-effective capture and transfer of human skills. Therefore, the aim of this research is to develop a framework for digitisation of manual manufacturing task knowledge, a major constituent of which is human skill. The proposed digitisation framework is based on the theory of human-workpiece interactions that is developed in this research. The unique aspect of the framework is the use of consumer-grade gaming interface technology to capture and record manual manufacturing tasks in digital form to enable the extraction, decoding and transfer of manufacturing knowledge constituents that are associated with the task. The framework is implemented, tested and refined using 5 case studies, including 1 toy assembly task, 2 real-life-like assembly tasks, 1 simulated assembly task and 1 real-life composite layup task. It is successfully validated based on the outcomes of the case studies and a benchmarking exercise that was conducted to evaluate its performance. This research contributes to knowledge in five main areas, namely, (1) the theory of human-workpiece interactions to decipher human behaviour in manual manufacturing tasks, (2) a cohesive and holistic framework to digitise manual manufacturing task knowledge, especially tacit knowledge such as human action and reaction skills, (3) the use of low-cost gaming interface technology to capture human actions and the effect of those actions on workpieces during a manufacturing task, (4) a new way to use hidden Markov modelling to produce digital skill models to represent human ability to perform complex tasks and (5) extraction and decoding of manufacturing knowledge constituents from the digital skill models

Motor contagion during human-human and human-robot interaction.

Motor resonance mechanisms are known to affect humans' ability to interact with others, yielding the kind of "mutual understanding" that is the basis of social interaction. However, it remains unclear how the partner's action features combine or compete to promote or prevent motor resonance during interaction. To clarify this point, the present study tested whether and how the nature of the visual stimulus and the properties of the observed actions influence observer's motor response, being motor contagion one of the behavioral manifestations of motor resonance. Participants observed a humanoid robot and a human agent move their hands into a pre-specified final position or put an object into a container at various velocities. Their movements, both in the object- and non-object- directed conditions, were characterized by either a smooth/curvilinear or a jerky/segmented trajectory. These trajectories were covered with biological or non-biological kinematics (the latter only by the humanoid robot). After action observation, participants were requested to either reach the indicated final position or to transport a similar object into another container. Results showed that motor contagion appeared for both the interactive partner except when the humanoid robot violated the biological laws of motion. These findings suggest that the observer may transiently match his/her own motor repertoire to that of the observed agent. This matching might mediate the activation of motor resonance, and modulate the spontaneity and the pleasantness of the interaction, whatever the nature of the communication partner