This article presents a human-centred design study examining how low-fidelity and embodied prototyping methods can elicit design-relevant knowledge for Robotic-Assisted Surgery (RAS). Focusing on femoral cement removal in Revision Total Hip Arthroplasty (rTHA), we conducted a design-led workshop involving a senior orthopaedic surgeon with expertise in complex revision cases, a surgical assistant, a robotics engineer from an industry partner developing orthopaedic surgical robots and a team of design researchers. Through scenario-based roleplay, task enactment and spatial configuration activities, we surfaced tacit, embodied and situated insights into anatomical factors, instrument design, surgeon-robot ergonomics, shared control models and operating theatre layout. These findings highlight challenges and opportunities for integrating robotic systems into complex surgical procedures and demonstrate how collaborative exploratory prototyping can support early stage reflection and interdisciplinary knowledge exchange. Rather than validating a specific solution, the study contributes both a transferable methodological approach for eliciting design insights in high-risk, highly constrained environments and formative insights into the design of RAS systems for rTHA.

This research investigates the application of tangible and embodied prototyping methods integrated with virtual simulation in Human-Robot Interaction (HRI). We present the development of the "kinematic puppet," a reliable, reusable, adaptable, and accessible prototyping tool designed to facilitate stakeholder engagement in early-stage HRI research and development without requiring significant financial or time investments. The potential of this methodological approach is illustrated through a formative co-design workshop in Robotic Assisted Surgery (RAS), where the kinematic puppet, simple props and a low-fidelity anatomical model enabled stakeholders to externalise tacit knowledge through roleplay scenarios. The case study suggests that combining physical and virtual approaches can support stakeholders in expressing concrete ideas for improving or changing the interaction, making abstract concepts tangible, with virtual simulation enabling rich data capture for further design development. This work contributes to the rapidly expanding toolbox of design approaches in HRI.

Bi-lateral communication between humans and robots is critical to their effective collaboration and the successful adoption of robotics in industry and as consumer products by the general public. While significant work has been done into communicating human intent to robots, less research has investigated conveying robotic intent to people. This study investigates the use of zoomorphic gestural communication on a commercially available Boston Dynamics Spot quadruped platform to determine if people can reliably recognise the robot’s intended actions from its movement. This is of particular interest as legged platforms bear much closer resemblance to living creatures than wheeled platforms or robotic arms and have not been thoroughly explored in research before. Specifically, we investigate whether ‘gestural building blocks’, based on the existing movement capabilities of the robot, can be composed together to successfully convey a range of intended gestural meanings to a person. To assess this, videos of four distinct gestural movement sequences related to a workplace inspection scenario were presented to participants who then completed a multi-choice survey and the Godspeed indices to measure their interpretation of each gesture and their overall impression of the robot across the key areas of anthropomorphism, likeability, perceived intelligence and perceived safety. Our results show that zoomorphic gestural communication using the existing gestural abilities of a quadruped robot produced successfully identified gestural meaning the majority of the time for all videos and that participants overall held positive attitudes towards the robot. This finding provides the groundwork for further exploration of the gestural communication modality for robots of this class.

This paper presents an account of using embodied composition as an approach to engage people in imagining robotic sound space. Embodied composition entails using bodily movements to produce a sequence of sounds. Semantic-free sound can play a useful communicative role in human-robot interaction. This includes robotic consequential sounds, i.e., sounds that robots inevitably make when moving, and the sonification of this movement. We bring together these topics and present a participatory, embodied approach that enables in-person investigation of robot consequential sound and movement sonification. We present three key insights about the approach based on three consecutive studies with a total of 29 participants. First, embodied composition engages participants' imagination of robotic sounds. Second, we found that movement, similar to listening, is tied to the individual and thereby leads to features and constraints for composition. Third, we found that sound can change people's experiences of the physical presence of the robot. Our discussion highlights that designing robot sounds benefits from a dialectical interaction approach. This offers a new direction for sound in human-robot interaction, relying not just on linear and functional design, but rather on designing for sound experiences.

Human-Robot Collaboration (HRC) has many potential benefits to workers in various sectors but also inherently changes work practices, processes, and ways of thinking. Lupetti et al. [2] argue that design techniques and processes are needed to bridge the gap between the technical research driving HRC approaches and the sociocultural reality and needs of end-users. This demo presents the ''kinematic puppet,'' a novel, cost-effective, modular, and adaptable tangible interface to facilitate embodied exploration of robotic movements and interactions through roleplaying and Wizard-of-Oz prototyping, enabling the exploration of HRC concepts without requiring advanced skills in robotic programming and supporting more human-centered design in HRC.

Extended reality (XR) technologies, encompassing virtual reality (VR), augmented reality (AR) and mixed reality (MR), have emerged as powerful visualisation mediums for enhancing the architectural design-fabrication process. AR has the practical relevance of streamlining on-site construction workflows by reducing errors, while its theoretical significance lies in its ability to transform traditional design and fabrication methodologies. AR can facilitate communications between humans, humans and robots during fabrication processes. In this paper, we examine three innovative case studies on the integration and utilisation of AR technology in architectural design-to-fabrication processes of collaborative tasks such as assembly and co-creation. First case study, uses AR overlays to facilitate human–human collaboration in implicit fabrication. Second case study explores the role of AR in supporting human–robot collaboration (HRC) for non-deterministic design processes. Third case study demonstrates how AR can enhance human–robot collaboration (HRC) in remote settings. By investigating these case studies, we provide insights into applied applications of AR in architectural contexts and the technology’s potential to support collaboration in architectural design-fabrication settings.

Bridging the gap between Artificial Intelligence (AI)-driven generative design and robotic fabrication remains a critical challenge in architectural automation. While Generative Artificial Intelligence (GenAI) tools have advanced conceptual design workflows, their practical deployment in physical construction is hindered by the absence of structured, fabrication-aware datasets to train suitable AI models. This study introduces GDRF (Geometric Data for Robotic Fabrication), an automated pipeline for the generation, evaluation, and encoding of structurally feasible brick wall designs, enabling the creation of machine-learning-compatible data tailored for architectural robotic assembly. We developed a six-stage process that combines parametric modeling, algorithmic design generation, physics-based simulation, data encoding and storage, toolpath generation and assembly simulation, and physical robotic assembly with a robot. Over 33,000 wall configurations were synthetically generated and evaluated for structural stability, of which approximately 52% met the feasibility criteria. Stable and failed designs were identified through displacement-based criteria and encoded using dot-product-based rotational representation, reducing dimensionality while preserving critical geometric features. Comparative analysis revealed that brute-force generation produced more consistent outcomes, while random sampling achieved slightly higher local diversity. This study delivered a data pipeline and the BrickNet dataset, providing a foundation for future research in generative design, structural prediction, and autonomous robotic assembly.

Augmented reality (AR)-enabled human–robot collaboration (HRC) is emerging as a critical paradigm in architectural design and fabrication, particularly for supporting real-time interaction, creative agency, and situated decision-making. As collaborative robots (cobots) become more integrated into exploratory design workflows, AR offers a means to bridge the gap between robotic precision and human intuition. This paper investigates how AR interfaces can facilitate adaptive, embodied collaboration between designers and cobots in spatially unconstrained, exploratory assembly tasks. We developed and evaluated an AR-enabled HRC system across two user studies involving architectural designers. The system allows users to preview, modify, and execute cobotic actions within a shared workspace, incorporating dynamic visual feedback and real-time spatial tracking. Drawing on principles of situated cognition and interactive fabrication, we analyse how AR supports spatial awareness, enhances user agency, and enables intuitive, adaptive interactions. The findings reveal that AR interfaces contribute to HRC through three interconnected themes: (1) improving predictive coordination by externalising cobot intentions and constraints, (2) reinforcing user agency via real-time decision-making tools, and (3) scaffolding situated learning through adaptive visual feedback. We conclude by outlining three key future directions: expanding the spatial and structural complexity of AR-HRC systems, developing more nuanced models of user-cobot interaction in design contexts, and integrating real-time structural feedback to inform user decision-making.

Current research in robotic sounds generally focuses on either masking the consequential sound produced by the robot or on sonifying data about the robot to create a synthetic robot sound. We propose to capture, modify, and utilise rather than mask the sounds that robots are already producing. In short, this approach relies on capturing a robot's sounds, processing them according to contextual information (e.g., collaborators' proximity or particular work sequences), and playing back the modified sound. Previous research indicates the usefulness of non-semantic, and even mechanical, sounds as a communication tool for conveying robotic affect and function. Adding to this, this paper presents a novel approach which makes two key contributions: (1) a technique for real-time capture and processing of consequential robot sounds, and (2) an approach to explore these sounds through direct human-robot interaction. Drawing on methodologies from design, human-robot interaction, and creative practice, the resulting 'Robotic Blended Sonification' is a concept which transforms the consequential robot sounds into a creative material that can be explored artistically and within application-based studies.

Co-designing represents a dynamic power shift where an underrepresented community, like the older population, can impact the responsible innovation of technology and its relationship with future generations. As such, through co-design, we can challenge the current stereotypes, technological inequalities and exclusions often assigned to older adults. Our research proposed a mixed approach to holistically understand the habituation of imaginaries, specifically socially interactive robots, in the context of older adults through their ageing experience. Based on our research process, this paper aims to critically reflect on the challenges and opportunities of Participatory Design with older adults for the speculative design of socially interactive robots. We advocate opening the discussion that recognises the importance of aligning technology with older adults’ values and needs beyond the realm of technology-led innovations.

The Architecture, Engineering, and Construction industry (AEC) is increasingly embracing automation, especially through advancements in Artificial Intelligence (AI). This paper proposes Levels of Automation (LOA) for architectural tasks, categorizing them into creative, documentation and planning, and physically demanding tasks. The study outlines LOA for each category, progressing from basic digital assistance to autonomous machine-driven operations in design and construction. Challenges and implications of varied automation levels are discussed, emphasizing dynamic task allocation based on context, available technology, and task complexity. Decision-making processes are examined concerning the suitability of AI and human intervention. Safety, adaptability, and task-specific considerations are highlighted in selecting suitable LOAs. This paper contributes to the ongoing discourse on automation in architecture, emphasizing the collaborative potential of humans and machines. As automation becomes inevitable in the AEC industry, selecting appropriate LOAs promises enhanced productivity, safety, cost-effectiveness, and overall project quality.

The emergence of collaborative robotics presents an opportunity for architectural designers to safely engage in design and fabrication through human-robot collaboration (HRC). By leveraging the adaptability, creativity, and design judgement of designers with the strength, repeatability, and design precision of robotic assistance, HRC has the potential to create a unified design-fabrication workflow. Recent advancements in augmented reality (AR) technology further enhance these prospects by enabling users to superimpose context-sensitive, computer-generated information in the real world. AR technology also provides situational awareness, which proves beneficial in the context of HRC. The maturation of AR technologies offers new possibilities for developing HRC systems tailored to architectural design-fabrication needs. Recognizing the pivotal role of human factors in HRC development process, this paper aims to explore the architectural designers’ needs to develop an AR-enabled HRC system that better supports the fabrication-centric design process, such as exploratory collaborative assembly tasks. Key findings highlight the necessity for a unified design-fabrication workflow, a clearer allocation of tasks between designers and robotic arms, an intuitive user interface, a streamlined interaction process, a better understanding of robot intentions and movements, intuitive procedures for error avoidance and correction, and enhanced user safety in HRC scenarios.

Rethinking conventional design and fabrication methods, this research presents a biomimetic fabrication-aware design workflow for building a lightweight pavilion. Exploring different natural organisms reveals that the optimized structures of diatoms (unicellular microalgae) could serve as a biological model to design a load-responsive lightweight pavilion. The interdisciplinary research outcome primarily involves translating diatoms' structural and symbolic logic to component modules populated on a given free-form shell. The generative design workflow enables the designer to continuously monitor quantitative metrics such as deflection, span length, number of components and joints, size and depth of components, and weight. The model is tightly intertwined with structural analysis and optimization results. The design algorithm utilizes Rhino, Grasshopper, incorporating essential plugins such as Karamba, Octopus, and Kangaroo. The proposed fabrication method is Robotic Incremental Sheet Forming (RISF), and the material is ultrathin aluminum sheets (0.3 mm thickness). This paper's focus is on the design phase of the research.

Human-Robot Collaboration (HRC) is an increasingly prominent topic in CSCW. From telepresence systems through field robots for extreme missions to social robots in homes, HRC is becoming a recurring theme across a broad range of CSCW research. Based on the growing interest, we explore the coupling of the field of CSCW and research on robotics at this critical time. This paper presents a primary and secondary literature review of CSCW proceedings and venues for robotics research. We identified 29 CSCW papers that contribute to the body of HRC research and analyse the foundations on which these papers rely. Then, we identified 138 papers published in robotics outlets that either (1) cite one or more CSCW papers, or (2) use the term CSCW. We discuss how CSCW is currently contributing to HRC research through five research topics: Sociomateriality, teamwork, awareness, embodiment, and communication. The paper contributes by offering three key future pathways for expanding this area of research, outlining questions and gaps that have yet to be explored for (1) expanding the application domains and diversifying robot types for HRC, (2) methodological implications for HRC, and (3) learning from human collaboration.

The emergence of collaborative robotics presents an opportunity for architectural designers to safely engage in design and fabrication through human-robot collaboration (HRC). By leveraging the adaptability, creativity, and design judgement of designers with the strength, repeatability, and design precision of robotic assistance, HRC has the potential to create a unified design-fabrication workflow. Recent advancements in augmented reality (AR) technology further enhance these prospects by enabling users to superimpose context-sensitive, computer-generated information in the real world. AR technology also provides situational awareness, which proves beneficial in the context of HRC. The maturation of AR technologies offers new possibilities for developing HRC systems tailored to architectural design-fabrication needs. Recognizing the pivotal role of human factors in HRC development process, this paper aims to explore the architectural designers' needs to develop an AR-enabled HRC system that better supports the fabrication-centric design process, such as exploratory collaborative assembly tasks. Key findings highlight the necessity for a unified design-fabrication workflow, a clearer allocation of tasks between designers and robotic arms, an intuitive user interface, a streamlined interaction process, a better understanding of robot intentions and movements, intuitive procedures for error avoidance and correction, and enhanced user safety in HRC scenarios.

With the arrival of the Industry 5.0 era, the empowerment of humans in human-robot collaboration (HRC) becomes a focal issue for HRC research and development. There is not yet a well-developed body of research and practice to determine whether applications of HRC are actually serving to empower humans. Unpacking this question requires a multifaceted approach with key contributions from diverse fields and disciplines including user modelling, adaptive interfaces, persistent communication, interaction design, human factors, and situational awareness. This workshop brings researchers and practitioners together to discuss when HRC empowers humans and when it does not, how the empowerment of human in HRC can be facilitated, the benefits of empowering humans in HRC, and who is empowered in HRC and who is not. We invite researchers and practitioners in Human-Computer Interaction, Robotics and Engineering, Ethics, Psychology, Social Sciences, Design, Architecture, and Artificial Intelligence, who work actively or wish to expand their knowledge and experience in HRC to take part in this timely discussion; an important step towards shaping the next-generation human-robot collaboration where both performance and quality of work are enhanced by people and robots working together.

Workpiece placement with respect to an industrial robot plays an important role in robotic manufacturing due to its influence on the configuration-dependent properties of industrial robots. Suboptimal placements of the workpiece may increase the required joint torques and decrease the dexterity of the robot. The focus of this work is to identify an optimal workpiece pose that enables a robot to carry out surface finishing with configurations that require the lowest possible joint torques while having maximum possible manipulability. We present a non-linear optimization-based algorithm to solve this problem and demonstrate the algorithm's capability on different workpieces which we share to facilitate further research in this area.

In efforts to disseminate research on human-robot interaction, many researchers use illustrations in the form of sketches, photographs, and 3D models of robot movements. These illustrations are not only useful for building on the research, but they also capture ways researchers think about robot movement. In this paper, we review papers from the ACM/IEEE International Conference on Human-Robot Interaction in which such illustrations are presented supplementary to the text. We analyse a total of 181 illustrations from 137 papers to understand the diverse ways in which robot movements are illustrated as well as how each style supports and limits information about the movements. We identify 10 basic styles that are used. Based on a visual analysis of these styles, we provide a detailed examination of each. This paper contributes with an overview that can be used to support future dissemination within the HRI research community. We present four aspects to consider for future illustrations and a discussion on how our findings could be utilised in early design processes.