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Paediatric congenital esophageal atresia surgery typically requires delicate and dexterous operations in a narrow and confined workspace. This study aims to develop a novel robot assisted surgical system to address these challenges.

The proposed surgical robot consists of two symmetrical slave arms with nine degree of freedoms each. Each slave arm uses a rigid-dexterous configuration and consists of a coarse positioning manipulator and a distal fine operation manipulator. A small Selective Compliance Assembly Robot Arm (SCARA) mechanism was designed to form the main component of the coarse positioning unit, ensuring to endure large forces along the vertical direction and meet the operational demands. The fine positioning manipulator applied the novel design using flexible shafts and universal joints to achieve delicate operations while possessing a high rigidity. The corresponding kinematics has been derived and then was validated by a co-simulation that was performed based on the combined use of Adams and MATLAB with considering the real robot mass information. Experimental evaluations for the tip positioning accuracy and the ring transfer tasks have been performed.

The simulation was performed to verify the correctness of the derived inverse kinematics and demonstrated the robot’s flexibility. The experimental results illustrated that the end-effector can achieve a positioning accuracy within 1.5 mm in a confined 30 × 30 × 30 mm workspace. The ring transfer task demonstrated that the surgical robot is capable of providing a solution for dexterous tissue intervention in a narrow workspace for paediatric surgery.

A novel and compact surgical assist robot is developed to support delicate operations by using the dexterous slave arm. The slave arm consists of a SCARA mechanism to avoid experiencing overload in the vertical direction and a tool manipulator driven by flexible shafts and universal joints to provide high dexterity for operating in a narrow workspace.

The purpose of this paper is to present a markerless human–manipulators interface which maps the position and orientation of human end-effector (EE, the center of the palm) to those of robot EE so that the robot could copy the movement of the operator hand.

The tracking system of this human–manipulators interface comprises five Leap Motions (LMs) which not only makes up the narrow workspace drawback of one LM but also provides redundancies to improve the data precision. However, because of the native noises and tracking errors of the LMs, the measurement errors increase over time. To address this problem, two filter tools are integrated to obtain the relatively accurate estimation of the human EE, that is, Particle Filter for position estimation and Kalman Filter for orientation estimation. Because the operator has inherent perceptive limitations, the motions of the manipulator may be out of sync with the hand motions, so that it is hard to complete with the high performance manipulation. Therefore, in this paper, an over-damping method is adopted to improve reliability and accuracy.

A series of human–manipulators interaction experiments were carried out to verify the proposed system. Compared with the markerless and contactless methods(Kofman et al., 2007; Du and Zhang, 2015), the method described in this study is more accurate and efficient.

The proposed method would not hinder most natural human limb motion and allows the operator to concentrate on his/her own task, making it perform high-precision manipulations efficiently.

Continuum manipulators are often used in complex and narrow space in recent years because of their flexibility and safety. Vision is considered to be one of the most direct methods to obtain its spatial shape. However, with the improvement of the cooperation requirements of multiple continuum manipulators and the increase of space limitation, it is impossible to obtain the complete spatial shape information of multiple continuum manipulators only by several cameras.

This paper proposes a fusion method using inertial navigation sensors and cameras to reconstruct the shape of continuum manipulators in the whole workspace. The camera is used to obtain the position information, and the inertial navigation sensor is used to obtain the attitude information. Based on the above two information, the shape of the continuum manipulator is reconstructed by fitting Bézier curve.

The experiment result of single continuum manipulator shows that the cubic Bézier curves is applicable to curve fitting of variable curvature, the maximum fitting error is about 2 mm. Meanwhile, the experiment result shows that this method is not affected by obstacles and can still reconstruct the shape of the continuum manipulators in 3-D space by detecting the position and attitude information of the end.

According to the authors’ knowledge, this is the first study on spatial shape reconstruction of multiple continuum manipulators and the first study to introduce inertial navigation sensors and cameras into the field of shape reconstruction of multiple continuum manipulators in narrow space. This method is suitable for shape reconstruction of manipulator with variable curvature continuum manipulator. When the vision of multiple continuum manipulators is blocked by obstacles, the spatial shape can still be reconstructed only by exposing the end point. The structure is simple, but it has certain accuracy within a certain range.

Aiming at presenting an interaction-free assembly assistance tool, the purpose of this paper is to propose a synchronous augmented reality (AR) assembly assistance and monitoring system. The system monitors operator’s hands activity and process completeness to recognize the assembly state, then display the AR contents contextually.

An assembly behavior recognition method is proposed based on gesture recognition. An assembly completeness inspection method is proposed based on SURF feature matching. Assembly state and AR display state are solved by a novel sequential hybrid AR display control strategy. A synchronous multi-channel AR view output strategy is proposed based on QR matrix decomposition.

A prototype system has been developed, and case study is performed on an industrial product. Experiments are performed to verify the feasibility, efficiency and recognition accuracy of the proposed methods.

The proposed system assists users to perform assembly tasks with automatic visual guidance and vision monitoring, avoiding distractions caused by redundant human–computer interactions.

All methods are integrated to work on only one head-worn device, making the proposed system portable and cheaper. The vision processing pipelines and the view output channels are reconfigurable for customization.

This paper proposes an interaction-free AR assembly assistance and monitoring system. Assembly behavior recognition and assembly completeness inspection methods are integrated to monitor the assembly state. A sequential hybrid AR display control strategy is proposed to contextually update the AR contents. A synchronous multi-channel AR view output strategy is proposed to fulfill different visualization needs.

The purpose of this paper is to review the National Plastics Exposition 2009, Plastics Show held in Chicago, IL, with emphasis on robots, end‐of‐arm‐tooling and their application in the plastics industry.

The approach takes the form of in‐depth interviews with suppliers of robots, injection molding machines, system integration of robots into plastic processing applications and suppliers of controls and end‐of‐arm‐tooling.

The plastic injection molding industry is moving to production cells with heavy usage of robot machine tending. The need for very short cycle times drives the interest in very fast agile robots with the ability to integrate easily into the production cell approach. New technologies such as in‐mold labeling also drive the need for suitable robots and competent system integrators to supply successful systems.

The paper shows that robot builders need to continue to develop specialized robots and tooling to match advancements in applications in the plastic industry. Users will need to think of robots as a necessary adjunct to any injection molding application.

This study aims to develop an interface management risk interaction modeling and analysis methodology applicable to complex systems in high-speed rail construction projects, reveal the interaction mechanism of interface management risk and provide theoretical support for project managers to develop appropriate interface management risk response strategies.

This paper introduces the association rule mining technique to improve the complex network modeling method. Taking China as an example, based on the stakeholder perspective, the risk factors and significant accident types of interface management of high-speed rail construction projects are systematically identified, and a database is established. Then, the Apriori algorithm is used to mine and analyze the strong association rules among the factors in the database, construct the complex network, and analyze its topological characteristics to reveal the interaction mechanism of the interface management risk of high-speed rail construction projects.

The results show that the network is both scale-free and small-world, implying that construction accidents are not random events but rather the result of strong interactions between numerous interface management risks. Contractors, technical interfaces, mechanical equipment, and environmental factors are the primary direct causal factors of accidents, while owners and designers are essential indirect causal factors. The global importance of stakeholders such as owners, designers, and supervisors rises significantly after considering the indirect correlations between factors. This theoretically explains the need to consider the interactions between interface management risks.

The interaction mechanism between interface management risks is unclear, which is an essential factor influencing the decision of risk response measures. This study proposes a new methodology for analyzing interface management risk response strategies that incorporate quantitative analysis methods and considers the interaction of interface management risks.

This paper aims to develop a specific type of mobile nonrigid support friction stir welding (FSW) robot, which can adapt to aluminum alloy trucks for rapid online repair.

The friction stir welding robot is designed to complete online repair according to the surface damage of large aluminum alloy trucks. A rotatable telescopic arm unit and a structure for a cutting board in the shape of a petal that was optimized by finite element analysis are designed to give enough top forging force for welding to address the issues of inadequate support and significant deformation in the repair process.

The experimental results indicate that the welding robot is capable of performing online surface repairs for large aluminum alloy trucks without rigid support on the backside, and the welding joint exhibits satisfactory performance.

Compared with other heavy-duty robotic arms and gantry-type friction stir welding robots, this robot can achieve online welding without disassembling the vehicle body, and it requires less axial force. This lays the foundation for the future promotion of lightweight equipment.

The designed friction stir welding robot is capable of performing online repairs without dismantling the aluminum alloy truck body, even in situations where sufficient upset force is unavailable. It ensures welding quality and exhibits high efficiency. This approach is considered novel in the field of lightweight online welding repairs, both domestically and internationally.

This paper aims to propose a general framework of shared control for human–robot interaction.

Human dynamics are considered in analysis of the coupled human–robot system. Motion intentions of both human and robot are taken into account in the control objective of the robot. Reinforcement learning is developed to achieve the control objective subject to unknown dynamics of human and robot. The closed-loop system performance is discussed through a rigorous proof.

Simulations are conducted to demonstrate the learning capability of the proposed method and its feasibility in handling various situations.

Compared to existing works, the proposed framework combines motion intentions of both human and robot in a human–robot shared control system, without the requirement of the knowledge of human’s and robot’s dynamics.

Office workspace is more than a place but one of the essential resources in business organizations. In recent years, research in office workspace management has become an increasingly important scholarly focus. However, there is a dearth of bibliometric studies to date on the subject. This study aims to explore a scientometric analysis of office workspace field.

The title/abstract/keyword search method was used to extract related papers from 1990 to 2018. A total of 1,670 papers published in Scopus were obtained and subjected to scientometric data analysis techniques via CiteSpace software.

The results revealed the active research institutions and countries, influential authors, important journals, representative references and research hotspots in this field.

While this study focused on office workspace management, the findings hold useful implications for the built environment in general and facility management in particular, being a sector that encompasses multiple disciplines involving building, office assets, people, processes and technology, which enable effective functioning of the built facilities.

This is probably the most comprehensive scientometric analysis of the office workspace field ever conducted. This study adds to the so far limited knowledge in the field and provides insights for future research.

This paper aims to present a kinematics analysis method and statics based control of the continuum robot with mortise and tenon joints to achieve better control performance of the robot.

The kinematics model is derived by the geometric analysis method under the piecewise constant curvature assumption, and the workspace and dexterity of the proposed robot are analyzed to optimize its structure parameters. Moreover, the statics model is established by the principle of virtual work, which is used to analyze the mapping relationship between the bending deformation and the applied forces/torques. To improve the control accuracy of the robot, a model-based controller is put forward.

Results of the experiments verify the feasibility of the proposed continuum structure and the correctness of the established model and the control method. The force deviation between the theoretical value and the actual value is relatively small, and the mean value of the deviation between the driving forces is only 0.46 N, which verify the established statics model and the controller.

The proposed model and motion controller can realize its accurate bending control with a few deviations, which can be used as the reference for the motion planning and dynamic model of the continuum robot.