Search Results (288)

This study presents the design, fabrication, and clinical validation of a lightweight, body-powered prosthetic index finger actuated via metacarpophalangeal (MCP) joint motion. The proposed system incorporates an underactuated, cable-driven mechanism combining rigid and compliant elements to achieve passive adaptability and embodied intelligence, supporting intuitive user interaction. Results indicate that the prosthesis successfully mimics natural finger flexion and adapts effectively to a variety of grasping tasks with minimal effort. This study was conducted in accordance with ethical standards and approved by the Institutional Review Board (IRB), Project No. 670161, titled “Biologically-Inspired Synthetic Finger: Design, Fabrication, and Application.” The findings suggest that the device offers a viable and practical solution for individuals with partial hand loss, particularly in settings where electrically powered systems are unsuitable or inaccessible. Full article

Mycelium is a living material that has gained popularity over the last decade in both architecture and design. Apart from understanding the physical behaviour of novel materials, it is also important to grasp how designers and the general audience perceive them. On the one hand, this study investigated mycelium growth in 3D-printed minimal surface shapes using a wood-based filament, and on the other hand, it examined how both designers and the general public experience interacting with mycelium. Using a material-driven design research method, a workshop with architecture students was conducted where various triply periodic minimal surfaces were designed and 3D printed. These shapes were used as molds and impregnated with mycelium, and the growth of mycelium was analyzed visually and photographically. Data on the experiences of the 30 workshop participants of working with mycelium was collected through a survey and analyzed qualitatively. After exhibiting results of the workshop in a public-facing exhibition, semi-structured interviews with members of the general public about their perceptions of mycelium were conducted. Three-dimensionally printed minimal surfaces with wood-based filaments can function as structural cores for mycelium-based composites, and the density of the minimal surface appears to influence mycelium growth, which binds to wood-based filaments. Students exhibited stronger feelings for living materials compared to non-living ones, displaying both biophilia and, to a lesser extent, biophobia. Introducing hands-on workshops with living and experimental materials in design studio settings can help future generations of designers develop sensibilities for, and a critical approach towards, the impact of their design decisions on the environment and sustainability. The study also contributes empirical data on how members of the general public perceive mycelium as a material for design. Full article

Grasping objects with a high degree of anthropomorphism is a critical component in the field of highly anthropomorphic robotic grasping. However, the accuracy of contact maps and the irrationality of the grasping gesture become challenges for grasp generation. In this paper, we propose a reasonably improved generation scheme, called Diffangle-Grasp, consisting of two parts: contact map generation based on a conditional variational autoencoder (CVAE), sharing the potential space with the diffusion model, and optimized grasping generation, conforming to the physical laws and the natural pose. The experimental findings demonstrate that the proposed method effectively reduces the loss in contact map reconstruction by 9.59% in comparison with the base model. Additionally, it enhances the naturalness by 2.15%, elevates the success rate of grasping by 3.27%, reduces the penetration volume by 11.06%, and maintains the grasping simulation displacement. The comprehensive comparison and qualitative analysis with mainstream schemes also corroborate the rationality of the improvement. In this paper, we provide a comprehensive account of our contributions to enhancing the accuracy of contact maps and the naturalness of grasping gestures. We also offer a detailed technical feasibility analysis for robotic human grasping. Full article

This paper presents platforms as a solution to rethink how we build, addressing the pressing paradox between meeting growing housing demands. The construction sector has not fully grasped the advantages of platforms beyond standardisation and efficiency. In contrast, other sectors have begun acknowledging that platforms can capture increased value through interactions among firms within a networked ecosystem. Learning from other sectors, this paper investigates platforms in the construction context, aiming to define, classify, and assess their impact on the construction value chain. The research approach was abductive, involving a cross-sectoral review of 190 platforms across 16 Australian and New Zealand Standard Industrial Classification (ANZSIC) industries and semi-structured interviews with stakeholder groups of the construction value chain in Australia. The findings categorise platforms as physical, digital, or hybrid, highlighting their potential to move value-added activities upstream, facilitate collaboration, and foster innovation through data-driven insights. The paper’s novelty lies in the exhaustive cross-sectoral review, the classification of platforms in the construction context, and the proposition of a platform approach as a versatile framework tailored to diverse needs and circumstances that offers a fresh perspective on sustainable building practices. The practical contribution of this study lies in offering guidelines for industry practitioners aiming to develop or refine a platform-based approach tailored to the construction context. Full article

This paper presents a Self-Learning Robotic System (SLRS) for healthcare assistance using Deep Imitation Learning (DIL). The proposed SLRS solution can observe and replicate human demonstrations, thereby acquiring complex skills without the need for explicit task-specific programming. It incorporates modular components for perception (i.e., advanced computer vision methodologies), actuation (i.e., dynamic interaction with patients and healthcare professionals in real time), and learning. The innovative approach of implementing a hybrid model approach (i.e., deep imitation learning and pose estimation algorithms) facilitates autonomous learning and adaptive task execution. The environmental awareness and responsiveness were also enhanced using both a Convolutional Neural Network (CNN)-based object detection mechanism using YOLOv8 (i.e., with 94.3% accuracy and 18.7 ms latency) and pose estimation algorithms, alongside a MediaPipe and Long Short-Term Memory (LSTM) framework for human action recognition. The developed solution was tested and validated in healthcare, with the aim to overcome some of the current challenges, such as workforce shortages, ageing populations, and the rising prevalence of chronic diseases. The CAD simulation, validation, and verification tested functions (i.e., assistive functions, interactive scenarios, and object manipulation) of the system demonstrated the robot’s adaptability and operational efficiency, achieving an 87.3% task completion success rate and over 85% grasp success rate. This approach highlights the potential use of an SLRS for healthcare assistance. Further work will be undertaken in hospitals, care homes, and rehabilitation centre environments to generate complete holistic datasets to confirm the system’s reliability and efficiency. Full article

The advent of mixed reality (MR) systems has revolutionized human–computer interactions by seamlessly integrating virtual elements with the real world. Devices like the HoloLens 2 (HL2) enable intuitive, hands-free interactions through advanced hand-tracking technology, making them valuable in fields such as education, healthcare, engineering, and training simulations. However, despite the growing adoption of MR, there is a noticeable lack of comprehensive comparisons between the hand-tracking accuracy of the HL2 and high-precision benchmarks like motion capture systems. Such evaluations are essential to assess the reliability of MR interactions, identify potential tracking limitations, and improve the overall precision of hand-based input in immersive applications. This study aims to assess the accuracy of HL2 in tracking hand position and measuring kinematic hand parameters, including joint angles and lateral pinch span (distance between thumb and index fingertips), using its tracking data. To achieve this, the Vicon motion capture system (VM) was used as a gold-standard reference. Three tasks were designed: (1) finger tracing of a 2D pattern in 3D space, (2) grasping various common objects, and (3) lateral pinching of objects with varying sizes. Task 1 tests fingertip tracking, Task 2 evaluates joint angle accuracy, and Task 3 examines the accuracy of pinch span measurement. In all tasks, HL2 and VM simultaneously recorded hand positions and movements. The data captured in Task 1 were analyzed to evaluate HL2’s hand-tracking capabilities against VM. Finger rotation angles from Task 2 and lateral pinch span from Task 3 were then used to assess HL2’s accuracy compared to VM. The results indicate that the HL2 exhibits millimeter-level errors compared to Vicon’s tracking system in Task 1, spanning in a range from 2 mm to 4 mm, suggesting that HL2’s hand-tracking system demonstrates good accuracy. Additionally, the reconstructed grasping positions in Task 2 from both systems show a strong correlation and an average error of 5°, while in Task 3, the accuracy of the HL2 is comparable to that of VM, improving performance as the object thickness increases. Full article

To correspond to the advancement of technology, programming has become an indispensable course in university curricula. However, students easily become confused by the rules governing program execution or by complex logical structures. Mastering program structure and logic often is a significant challenge for beginners, especially. Despite the availability of information on programming on various websites and tools, including generative artificial intelligence (AI), there is still a gap between conceptual understanding and practical application for beginners. They overlook important implementation details or struggle to grasp the flow of a program, making the mastery of program logic a persistent challenge. To address these issues, we have developed a system that dynamically generates process architecture diagrams. Users upload their code, and the system produces corresponding diagrams that decompose and execute the code line by line. Its visual representation allows users to observe the program’s execution and aids them in comprehending the sequence and operational flow of the code. By understanding the structure and logic of the program intuitively, this system supplements traditional teaching methods and AI-assisted question-and-answer tools. The experimental results demonstrated that students found the system helpful to track their learning progress (87%) and improved their understanding of program code (81%). Additionally, 84% of students reported that the system was easy to use, highlighting its user-friendliness. In terms of student interest, 83% of students agreed that the interactive elements made learning more engaging, indicating that the system positively contributed to dynamic and enjoyable learning. However, 63% of students reported an improvement in coding and were influenced by the complexity of the programming tasks assigned. Despite this, the overall satisfaction with the system developed in this study was high. Full article

This research study investigates the impact of a virtual dashboard on the quality of task execution in robotic teleoperation. More specifically, this study investigates how a virtual dashboard improves user awareness and grasp precision in a teleoperated pick-and-place task by providing users with critical information in real-time. An experiment was conducted with 30 participants in a robotic teleoperated task to measure their task performance in two different experimental conditions: a control group used conventional interfaces, and an experimental group utilized the virtual dashboard with additional information. Research findings indicate that integrating a virtual dashboard improves grasping accuracy, reduces user fatigue, and speeds up task completion, thereby improving task effectiveness and the quality of the experience. Full article

Cancer metastasis constitutes a multifactorial phenomenon that continues to confound therapeutic strategies. The biochemical signals governing motile phenotypes have been extensively characterized, but mechanobiological interactions have only recently been integrated into cancer cell motility models and remain less well elucidated. The identification of the biochemically and mechanically controlled epithelial–mesenchymal transition (EMT) of cancer cells, which occurs either completely or partially, has led to a major breakthrough and a universal phenomenon in cancers. In addition, a relatively new theory based on mechanobiological aspects called “jamming-to-unjamming transition” is being proposed to explain the transition of cancer cells to an invasive phenotype. The latter transition may help to better understand the different types of 3D migration and invasion of cancer cells. Similarly to EMT, the transition from jamming to unjamming seems to be controlled by molecular and physical factors, including cell mechanics and mechanical cues from the extracellular matrix (ECM) of the tumor microenvironment (TME). It is challenging to grasp the distinctions between the transition from jamming to unjamming and EMT, as they appear to be the same at first glance. However, upon closer examination, the two transitions are quite separate. Moreover, it is still unclear whether both transitions may act synergistically. This review highlights the most important breakthroughs in the transition from jamming to unjamming, with a focus on mechanobiology and extracellular environmental aspects, and it compares them with those of EMT. In addition, the impact of the TME, such as ECM scaffold and cancer-associated fibroblasts (CAFs) on the jamming-to-unjamming transition is discussed. Finally, the research frontiers and future directions in the field of mechanobiological research in cancer metastasis are outlined. Full article

This study proposes a GPU-accelerated Position-Based Dynamics (PBD) system for realistic and interactive cloth simulation in Extended Reality (XR) environments, and comprehensively evaluates its performance and functional capabilities on standalone XR devices, such as the Meta Quest 3. To overcome the limitations of traditional CPU-based physics simulations, we designed and optimized highly parallelized algorithms utilizing Unity’s Compute Shader framework. The proposed system achieves real-time performance by implementing efficient collision detection and response handling with complex environmental meshes (RoomMesh) and dynamic hand meshes (HandMesh), as well as capsule colliders based on hand skeleton tracking (OVRSkeleton). Performance evaluations were conducted for both single-sided and double-sided cloth configurations across multiple resolutions. At a 32 × 32 resolution, both configurations maintained stable frame rates of approximately 72 FPS. At a 64 × 64 resolution, the single-sided cloth achieved around 65 FPS, while the double-sided configuration recorded approximately 40 FPS, demonstrating scalable quality adaptation depending on application requirements. Functionally, the GPU-PBD system significantly surpasses Unity’s built-in Cloth component by supporting double-sided cloth rendering, fine-grained constraint control, complex mesh-based collision handling, and real-time interaction with both hand meshes and capsule colliders. These capabilities enable immersive and physically plausible XR experiences, including natural cloth draping, grasping, and deformation behaviors during user interactions. The technical advantages of the proposed system suggest strong applicability in various XR fields, such as virtual clothing fitting, medical training simulations, educational content, and interactive art installations. Future work will focus on extending the framework to general deformable body simulation, incorporating advanced material modeling, self-collision response, and dynamic cutting simulation, thereby enhancing both realism and scalability in XR environments. Full article

Botanical richness and diversity play crucial roles in regulating ecosystem functions and contribute to the sustainable intensification of perennial grasslands. This approach can be achieved through simultaneous or partial production of grasses in the same field, leading to enhanced productivity, reduced dependence on inorganic fertilizers and pesticides, and mitigating effects of edaphoclimatic variations. However, the existing literature predominantly focuses on associations between forage grasses and legumes or annual species. Furthermore, the subject should be explored under tropical conditions and environments, particularly considering the associations among well-managed perennial forage grasses. The interaction among perennial tropical forage grasses presents an alternative for exploration in the tropics, given the vast diversity of species and genotypes available. This review discusses the existing literature on multispecific pastures, elucidating the potential benefits for pastoral ecosystems. The association of perennial tropical forage grasses represents an emerging research area offering strategic opportunities for the sustainable intensification of animal production systems. Mixed pastures may be an economical and ecological alternative and enhance the production and sustainability of forage systems in the tropics. However, challenges persist in selecting plant species to achieve multifunctionality and understanding the underlying mechanisms shaping botanical diversity and productive performance within an association. This review emphasizes that understanding the morphological and agronomic characteristics of species and genotypes intended for cultivation in association is key to grasping the dynamics of competition for aboveground and belowground resources and creating combinations that deliver specific ecosystem services. Full article

The interactive grasp of robots can grasp the corresponding objects according to the user’s choice. Most interactive grasp methods based on deep learning comprise visual language and grasp detection models. However, in existing methods, the trainability and generalization ability of the visual language model is weak, and the robot cannot cope well with grasping small target objects. Therefore, this paper proposes a 6-DoF grasp detection method guided by visual language, which converts text instructions and RGBD images of the scene to be grasped into inputs and outputs for the 6-DoF grasp posture of the object corresponding to the text instructions. In order to improve the trainability and feature extraction ability of the visual language model, a multi-head attention mechanism combined with hybrid normalization is designed. At the same time, a local attention mechanism is introduced into the grasp detection model to enhance the global and local information interaction ability of point cloud data, thereby improving the grasping ability of the grasp detection model for small target objects. The method proposed in this paper first uses the improved visual language model to predict the plane position information of the target object, then uses the improved grasp detection model to predict all the graspable postures in the scene, and finally uses the plane position information to filter out the graspable postures of the target object. The visual language model and grasp detection model proposed in this paper have achieved excellent performance in various scenarios of public datasets while ensuring a specific generalization ability. In addition, we also conducted real grasp experiments, and the 6-DoF grasp detection method based on visual language guidance proposed in this paper achieved a grasp success rate of 95%. Full article

Understanding the complexity of urban systems remains a significant challenge for researchers and practitioners in urban planning and governance. Cities function as multifaceted systems composed of interconnected subsystems with nonlinear interactions, making the design of effective interventions to enhance sustainability and liveability particularly challenging. Spatial modelling has gained prominence in recent decades, fuelled by advances in digital technologies and the advent of digital twins as decision support tools. To fully harness these innovations, it is essential to grasp their underlying principles, strengths, and limitations, and to select the most suitable modelling approach for specific applications. This paper examines two contrasting spatial modelling paradigms: top-down and bottom-up. Specifically, it focuses on Space Syntax and Agent-Based Modelling as representative tools of each approach, analyzing their potential applications in urban planning. This discussion delves into the effectiveness of the proposed methodologies in analyzing crime dynamics—selected as a representative application field—at the micro-urban scale. It highlights the insights each approach offers, emphasizing their contributions to understanding the spatial and environmental factors influencing crime patterns. Finally, this paper explores the potential for integrating these methodologies to develop hybrid models that capture both spatial structure and emergent behaviours, offering enhanced support for sustainable urban policies and planning. Full article

Soft anthropomorphic robotic grippers are attractive because of their inherent compliance, allowing them to adapt to the shape of grasped objects and the overload protection needed for safe human–robot interaction or gripping delicate objects with sophisticated control. The anthropomorphic design allows the gripper to benefit from the biological evolution of the human hand to create a multi-functional robotic end effector. Entirely soft grippers could be more efficient because they yield under high loads. A trending solution is a hybrid gripper combining soft and rigid elements. This work describes a prototype of an anthropomorphic, underactuated five-finger gripper with a direct pneumatic drive from soft bending actuators and an integrated resistive tactile sensor array. It is a hybrid construction with soft robotic structures and rigid skeletal elements, which reinforce the body, focus the direction of the actuator’s movement, and make the finger joints follow the forward kinematics. The hand is equipped with a resistive tactile dielectric elastomer sensor array that directly triggers the hand’s actuation in the sense of reflexes. The hand can execute precision grips with two and three fingers, as well as lateral grip and strong grip types. The softness of the actuation allows the finger to adapt to the shape of the objects. Full article

Soft robots are advantageous due to their flexibility, ability to interact with humans, and multifunctional adaptability. However, developing soft robots that are unrestrained and can be reprogrammed for reversible control without causing damage remains a significant challenge. The majority of soft robots have a bilayer structure with internal stress, which limits their motion to pre-programmed anisotropic structures. Taking inspiration from pillworms found in nature, we propose an approach for controlling and reprogramming the motion of actuators using infrared light as the driver and a laser-melted paraffin wax (PW) shell as the controller. The dual-purpose shell can not only protect the actuator but can also alter its initial motion behavior to achieve multiple programming, profile modeling, object grasping, and directional crawling tasks, thereby enabling active changes to the motion strategy in response to external stimuli. This method can also be extended to other materials with similar properties and multi-stimulus responses, offering a new pathway for developing unconstrained, autonomous soft robots and intelligent devices. Full article