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This paper aims to present an impedance control method with mixed H₂/H_∞ synthesis and relaxed passivity for a cable-driven series elastic actuator to be applied for physical human–robot interaction.

To shape the system’s impedance to match a desired dynamic model, the impedance control problem was reformulated into an impedance matching structure. The desired competing performance requirements as well as constraints from the physical system can be characterized with weighting functions for respective signals. Considering the frequency properties of human movements, the passivity constraint for stable human–robot interaction, which is required on the entire frequency spectrum and may bring conservative solutions, has been relaxed in such a way that it only restrains the low frequency band. Thus, impedance control became a mixed H₂/H_∞ synthesis problem, and a dynamic output feedback controller can be obtained.

The proposed impedance control strategy has been tested for various desired impedance with both simulation and experiments on the cable-driven series elastic actuator platform. The actual interaction torque tracked well the desired torque within the desired norm bounds, and the control input was regulated below the motor velocity limit. The closed loop system can guarantee relaxed passivity at low frequency. Both simulation and experimental results have validated the feasibility and efficacy of the proposed method.

This impedance control strategy with mixed H₂/H_∞ synthesis and relaxed passivity provides a novel, effective and less conservative method for physical human–robot interaction control.

Librarians are challenged by technology transformations in research data metrics to re-position in the evolving cycles of research production, communication and evaluation. They are also are challenged by the new and emerging strategic needs of universities for data-driven research intelligence that provides a comparative edge in the global world of higher education. This paper aims to discover how libraries can support universities in applying international assessment standards by delivering new reference and information services based on data analytics.

This paper focuses on a new reference and information service Research Data Analytics in China that was launched in 2017. There is a discussion of how new university needs have provided the strategic drive for librarians to develop skills.

The Research Data Analytics service development is significant for showcasing a new role for librarians in relation to research data evaluation metrics linked to publication strategies for authors and strategic intelligence for institutions. This has driven the development of the library’s position and influence in strategic research intelligence services.

The future for librarians is about being adventurous. Librarians are experts who will sparkle and shine beyond the bubble of the library walls. They can demonstrate a commitment to supporting university colleagues in professional services and academia to blossom and flourish. Distinctive visual technologies can be adopted for exploring research data which transform research production, communication and evaluation and therefore transform our position and future through technology-enabled innovations.

Robots face fundamental challenges in achieving reliable and stable operations for complex home service scenarios. This is one of the crucial topics of robotics methods to imitate human beings’ advanced cognitive characteristics and apply them to solve complex tasks. The purpose of this study is to enable robots to have the ability to understand the scene and task process in complex scenes and to provide a reference method for robot task programming in complex scenes.

This paper constructs a task modeling method for robots in complex environments based on the characteristics of the perception-motor memory model of human cognition. In the aspect of episodic memory construction, the task execution process is included in the category of qualitative spatio-temporal calculus. The topology interaction of objects in a task scenario is used to define scene attributes. The task process can be regarded as changing scene attributes on a time scale. The qualitative spatio-temporal activity graphs are used to analyze the change process of the object state with time during the robot task execution. The tasks are divided according to the different values of scene attributes at different times during task execution. Based on this, in procedural memory, an object-centered motion model is developed by analyzing the changes in the relationship between objects in the scene episode by analyzing the scene changes before and after the robot performs the actions. Finally, the task execution process of the robot is constructed by alternately reconstructing episodic memory and procedural memory.

To verify the applicability of the proposed model, a scenario where the robot combines the object (one of the most common tasks in-home service) is set up. The proposed method can obtain the landscape of robot tasks in a complex environment.

The robot can achieve high-level task programming through the alternating interpretation of scenarios and actions. The proposed model differs from traditional methods based on geometric or physical feature information. However, it focuses on the spatial relationship of objects, which is more similar to the cognitive mechanism of human understanding of the environment.

Walking-aid exoskeletons can assist and protect effectively the group with lower limb muscle strength decline, workers, first responders and military personnel. However, there is almost no united control strategy that can effectively assist daily walking. This paper aims to propose a hybrid oscillators’ (HOs) model to adapt to irregular gait (IG) patterns (frequent alternation between walking and standing or rapid changing of walking speed, etc.) and generate compliant and no-delay assistive torque.

The proposed algorithm, HOs, combines adaptive oscillators (AOs) with phase oscillator through switching assistive mode depending on whether or not the AOs' predicting error of hip joint degree is exceeded our expectation. HOs can compensate for delay by predicting gait phase when in AOs mode. Several treadmill and free walking experiments are designed to test the adaptability and effectiveness of HOs model under IG.

The experimental results show that the assistive strategy based on the HOs is effective under IG patterns, and delay is compensated totally under quasiperiodic gait conditions where a smoother human–robot interaction (HRI) force and the reduction of HRI force peak are observed. Delay compensation is found very effective at improving the performance of the assistive exoskeleton.

A novel algorithm is proposed to improve the adaptability of a walking assist hip exoskeleton in daily walking as well as generate compliant, no-delay assistive torque when converging.

This study aims to examine the effects on student motivation and perception of technological interventions within undergraduate mechanical engineering and product design and manufacture programs at a Sino-foreign international university. The authors use an augmented reality game application within a class on Design for Manufacturing and Assembly (DfMA) that was developed using the approaches of microlearning and digital game-based learning (DGBL).

Structured as design-based research, the study reports on developing innovative educational interventions and provides an empirical investigation of their effectiveness. Data were collected using a mixed methods approach, using pre- and post-tests and questionnaires, together with researcher observations and participant interviews.

Through two rounds of playtests, the game positively affected intrinsic motivation and encouraged higher-order cognitive learning, critical thinking, communication and collaboration. Collaborative learning plays a significant role, DGBL is preferred over traditional methods and microlearning reduces information density and cognitive overload.

The study contributes to our understanding of digital game-based interventions on students’ intrinsic motivation and provides insights into effective ways to design instructional materials in similar teaching and learning settings.

This paper aims to understand the trade transportation situation between China and Koreas, and to explore the possibility of establishing the surface transportation corridor between China and Koreas in the future. Moreover, the paper also intends to find out the mode choice behaviors of shippers, which can be used to analyze the substitute effects of the surface modes on the water one.

The paper first analyzes the Sino-Korean bilateral trade and the corresponding trade transportation between China and Koreas. Secondly, it presents the surface transportation network between China and Koreas, and analyzes the warming relations between the North and South. Finally, the modal split of trade transportation between China and Koreas is estimated by establishing a mode choice model based on a questionnaire survey.

With the increasingly stable political environment and the physical highway and railway connections, the surface transportation network would become possible. Moreover, the shippers need the multimodal transportation system between China and Koreas, and many shippers would select road or rail mode if a suitable road or rail network were available. Especially, between China and South Korea, the road, rail and water mode may be used evenly, while the road mode may play a more important role between China and North Korea. The surface modes would have a huge substitute effect on the water mode.

The existing literature conducted research mainly from the perspective of economy and geopolitics, while the topics of transportation between China and Koreas are rarely concerned. This paper intends to throw some light on the situation of the trade transportation between China and Koreas, consider the potential of relation improvement on the Korean Peninsula proactively and study the surface transportation issues between China and Koreas.

A large number of residential buildings in hot summer and cold winter zone of China are non-energy efficient with poor indoor thermal conditions. Retrofitting residential buildings with energy efficiency measures is thus important for residents. However, this work progressed slowly because practically applicable measures that not only have high energy savings but also improve indoor thermal performance have not been studied. Thus, this paper carried out a simulation study on the selection of suitable energy saving measures for residential buildings in hot summer and cold winter zone of China. Five potential energy saving options are considered and the energy, indoor thermal comfort and economic performance are compared. The results show that adding movable solar shades is the optimum option with all performance indices ranking first. Meanwhile, this measure is also the only acceptable energy saving solution for residents since its payback period is less than the lifespan of a building. As a conclusion, it is recommended to use movable solar shades as a first priority when retrofitting residential buildings.

To make the robot that have real autonomous ability is always the goal of mobile robot research. For mobile robots, simultaneous localization and mapping (SLAM) research is no longer satisfied with enabling robots to build maps by remote control, more needs will focus on the autonomous exploration of unknown areas, which refer to the low light, complex spatial features and a series of unstructured environment, lick underground special space (dark and multiintersection). This study aims to propose a novel robot structure with mapping and autonomous exploration algorithms. The experiment proves the detection ability of the robot.

A small bio-inspired mobile robot suitable for underground special space (dark and multiintersection) is designed, and the control system is set up based on STM32 and Jetson Nano. The robot is equipped with double laser sensor and Ackerman chassis structure, which can adapt to the practical requirements of exploration in underground special space. Based on the graph optimization SLAM method, an optimization method for map construction is proposed. The Iterative Closest Point (ICP) algorithm is used to match two frames of laser to recalculate the relative pose of the robot, which improves the sensor utilization rate of the robot in underground space and also increase the synchronous positioning accuracy. Moreover, based on boundary cells and rapidly-exploring random tree (RRT) algorithm, a new Bio-RRT method for robot autonomous exploration is proposed in addition.

According to the experimental results, it can be seen that the upgraded SLAM method proposed in this paper achieves better results in map construction. At the same time, the algorithm presents good real-time performance as well as high accuracy and strong maintainability, particularly it can update the map continuously with the passing of time and ensure the positioning accuracy in the process of map updating. The Bio-RRT method fused with the firing excitation mechanism of boundary cells has a more purposeful random tree growth. The number of random tree expansion nodes is less, and the amount of information to be processed is reduced, which leads to the path planning time shorter and the efficiency higher. In addition, the target bias makes the random tree grow directly toward the target point with a certain probability, and the obtained path nodes are basically distributed on or on both sides of the line between the initial point and the target point, which makes the path length shorter and reduces the moving cost of the mobile robot. The final experimental results demonstrate that the proposed upgraded SLAM and Bio-RRT methods can better complete the underground special space exploration task.

Based on the background of robot autonomous exploration in underground special space, a new bio-inspired mobile robot structure with mapping and autonomous exploration algorithm is proposed in this paper. The robot structure is constructed, and the perceptual unit, control unit, driving unit and communication unit are described in detail. The robot can satisfy the practical requirements of exploring the underground dark and multiintersection space. Then, the upgraded graph optimization laser SLAM algorithm and interframe matching optimization method are proposed in this paper. The Bio-RRT independent exploration method is finally proposed, which takes shorter time in equally open space and the search strategy for multiintersection space is more efficient. The experimental results demonstrate that the proposed upgrade SLAM and Bio-RRT methods can better complete the underground space exploration task.

This article aims to develop and validate a theoretical model via survey data to identify the affordances and challenges influencing metaverse adoption. We specifically examine the impact of immersion on users' adoption decisions and identify which affordances predict this immersion. Additionally, this paper assesses the importance of perceived risks in users' decision-making processes regarding future metaverse engagement.

Using regression models applied to 198 survey responses, we tested our proposed model. To deepen our insights, we also conducted a qualitative analysis.

The findings confirm that users' perceptions of immersion and perceived risks are critical determinants in adoption decisions. Social presence, influenced by factors such as ubiquity and interoperability, emerges as a key component of immersion. From the qualitative data, we identified two potential strategies to enhance metaverse immersion: technical improvements and offline device-assisted strategies.

Our study contributes to the literature on information systems (IS) adoption and provides practical insights for practitioners on crucial considerations in metaverse design.