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This paper aims to present a prototype of medical transportation robot whose positioning accuracy can reach millimeter-level in terms of patient transportation. By using this kind of mobile robot, a fully automatic image diagnosis process among independent CT/PET devices and the image fusion can be achieved.

Following a short introduction, a large-load 4WD-4WS (four-wheel driving and four-wheel steering) mobile robot for carrying patient among multiple medical imaging equipments is developed. At the same time, a specially designed bedplate with self-locking function is also introduced. For further improving the positioning accuracy, the authors proposed a calibration method based on Gaussian process regression (GPR) to process the measuring data of the sensors. The performance of this robot is verified by the calibration experiment and Image fusion experiment. Finally, concluding comments are drawn.

By calibrating the robot’s positioning system through the proposed GPR method, one can obtain the accuracy of the robot’s offset distance and deflection angle, which are 0.50 mm and +0.21°, respectively. Independent repeated trials were then set up to verify this result. Subsequent phantom experiment shows the accuracy of image fusion can be accurate within 0.57 mm in the front-rear direction and 0.83 in the left-right direction, respectively, while the clinical experiment shows that the proposed robot can practically realize the transportation of patient and image fusion between multiple imaging diagnosis devices.

The proposed robot offers an economical image fusion solution for medical institutions whose imaging diagnosis system basically comprises independent MRI, CT and PET devices. Also, a fully automatic diagnosis process can be achieved so that the patient’s suffering of getting in and out of the bed and the doctor’s radiation dose can be obviated.

The general bedplate presented in Section 2 that can be mounted on the CT and PET devices and the self-locking mechanism has realized the catching and releasing motion of the patient on different medical devices. They also provide a detailed method regarding patient handling and orientation maintenance, which was hardly mentioned in previous research. By establishing the positioning system between the robot and different medical equipment, a fully automatic diagnosis process can be achieved so that the patient’s suffering of getting in and out of the bed and the doctor’s radiation dose can be obviated.

The GPR-based method proposed in this paper offers a novel method for enhancing the positioning accuracy of the industrial AGV while the transportation robot proposed in this paper also offers a solution for modern imaging fusion diagnosis, which are basically predicated on the conjoint analysis between different kinds of medical devices.

This paper aims to present an open-architecture kinematic controller, which was developed for articulated robots, facing the demands of various applications and low cost on robot system.

A general approach to develop this controller is described in hardware and software design. The hardware consists of embedded boards and programable multi-axes controller (PMAC), connected with ethernet, and the software is implemented on a robot operating system with MoveIt!. The authors also developed a teach pendant running as a LAN node to provide a human–machine interface (HMI).

The proposed approach was applied to several real articulated robot systems and was proved to be effective and portable. The proposed controller was compared with several similar systems to verify its integrality and flexibility. The openness of this controller was discussed and is summarized at the end of this paper.

The proposed approach provided an open and low-complex solution for experimental studies in the lab and short-run production in small workshops.

Several contributions are made by the research. The actuation model and communication were implemented to integrate the trajectory planning module and PMAC for setting up the physical interface. Method and program interface based on kinematics was provided to generate various interpolations for trajectory planning. A teach pedant with HMI was developed for controlling and programing the robot.

This paper aims to present a new method to analyze the robot’s obstacle negotiation based on the terramechanics, where the terrain physical parameters, the sinkage and the slippage of the robot are taken into account, to enhance the robot’s trafficability.

In this paper, terramechanics is used in motion planning for all-terrain obstacle negotiation. First, wheel/track-terrain interaction models are established and used to analyze traction performances in different locomotion modes of the reconfigurable robot. Next, several key steps of obstacle-climbing are reanalyzed and the sinkage, the slippage and the drawbar pull are obtained by the models in these steps. In addition, an obstacle negotiation analysis method on loose soil is proposed. Finally, experiments in different locomotion modes are conducted and the results demonstrate that the model is more suitable for practical applications than the center of gravity (CoG) kinematic model.

Using the traction performance experimental platform, the relationships between the drawbar pull and the slippage in different locomotion modes are obtained, and then the traction performances are obtained. The experimental results show that the relationships obtained by the models are in good agreement with the measured. The obstacle-climbing experiments are carried out to confirm the availability of the method, and the experimental results demonstrate that the model is more suitable for practical applications than the CoG kinematic model.

Comparing with the results without considering Terramechanics, obstacle-negotiation analysis based on the proposed track-terrain interaction model considering Terramechanics is much more accurate than without considering Terramechanics.

This paper aims to propose a robotic automation system for processing special-shaped thin-walled workpieces, which includes a measurement part and a processing part.

In the measurement part, to efficiently and accurately realize the three-dimensional camera hand-eye calibration based on a large amount of measurement data, this paper improves the traditional probabilistic method. To solve the problem of time-consuming in the extraction of point cloud features, this paper proposes a point cloud feature extraction method based on seed points. In the processing part, the authors design a new type of chamfering tool. During the process, the robot adopts admittance control to perform compensation according to the feedback of four sensors mounted on the tool.

Experiments show that the proposed system can make the tool smoothly fit the chamfered edge during processing and the machined chamfer meets the processing requirements of 0.5 × 0.5 to 0.9 × 0.9 mm².

The proposed design and approach can be applied on many types of special-shaped thin-walled parts. This will give a new solution for the automation integration problem in aerospace manufacturing.

A novel robotic automation system for processing special-shaped thin-walled workpieces is proposed and a new type of chamfering tool is designed. Furthermore, a more accurate probabilistic hand-eye calibration method and a more efficient point cloud extraction method are proposed, which are suitable for this system when comparing with the traditional methods.

The paper aims to present a tracked robot comprised of several biochemical sampling instruments and a universal control architecture. In addition, a dynamic motion planning strategy and autonomous modules in sampling tasks are designed and illustrated at length.

Several sampling instruments with position tolerance and sealing property are specifically developed, and a robotic operation system (ROS)-based universal control architecture is established. Then, based on the system, two typical problems in sampling tasks, i.e. arm motion planning in unknown environment and autonomous modules, are discussed, implemented and tested. Inspired by the idea of Gaussian process classification (GPC) and Gaussian process (GP) information entropy, three-dimensional (3D) geometric modeling and arm obstacle avoidance strategy are implemented and proven successfully. Moreover, autonomous modules during sampling process are discussed and realized.

Smooth implementations of the two experiments justify the validity and extensibility of the robot control scheme. Furthermore, the former experiment proves the efficiency of arm obstacle avoidance strategy, while the later one demonstrates the time reduction and accuracy improvement in sampling tasks as the autonomous actions.

The proposed control architecture can be applied to more mobile and industrial robots for its feasible and extensible scheme, and the utility function in arm path planning strategy can also be utilized for other information-driven exploration tasks.

Several specific biochemical sampling instruments are presented in detail, while ROS and Moveit! are integrated into the system scheme, making the robot extensible, achievable and real-time. Based on the control scheme, an information-driven path planning algorithm and automation in sampling tasks are conceived and implemented.

The paper aims to improve the radiation-proof capability of the self-designed mobile robot with a 7-DOF manipulator, enabling the long-playing inspection and intervention under high-dose radiation environment. In this context, gamma-ray irradiation test for electronic components and specific hardness design have also been specifically presented and discussed.

The study’s hardness design mainly focuses on shielding protection, distance protection and time protection. Irradiation test is first carried out to investigate irradiation resistance of each electronic module. Then, modular deployment and shielding calculation are completed for the point-type nuclear accidents, respectively, to achieve a robust anti-radiation design scheme. Finally, the field experiment is conducted to validate system effectiveness and good mobility, and operational practices are acquired for the realization of time protection.

Coupled with modular redeployment and shielding design, irradiation results illustrate the effectiveness of robotic anti-radiation design. Meanwhile, experiences and reformed measures from the field exercise implement efficient operation and radiological time protection.

Considering the huge risks of high-dose source exposure, the radiation-resistance of the overall system cannot be verified in the field experiment. Fortunately, irradiation test and modular shielding calculation are conducted as a minimal validation.

The proposed anti-radiation design methods and the irradiated results can be applied to many other nuclear vehicles and manipulators for the feasible multi-layer protection and excellent mobility.

A nuclear intervention robot with specific hardness design is presented in detail in this paper. Enlightened by the idea of shielding and distance protection, a large number of electronic modules with multiple types and structures are treated and compared in irradiation experiments, while modular redeployment and retrofitting are completed to reduce irradiated damages. To achieve the effect of time protection, mobility performance and operational practices are discussed and validated in the field experiment based on the mobile system.

The purpose of this paper is to propose a new smooth online near time‐optimal trajectory planning approach to reduce the consuming time compared to the conventional dynamics trajectory planning methods.

In the proposed method, the robot path is expressed by a scalar path coordinate. The joints torque boundary and speed boundary are transformed into the plane, which can generate the limitation curves of pseudo‐velocity. The maximum pseudo‐velocity curve that meets the limits of torque and speed is built up through the feature points and control points in the plane by using cubic polynomial fitting method. Control points used for cubic polynomial construction are optimized by the Golden‐Section method.

The proposed method can avoid Range's phenomenon and also guarantee the continuity of torque.

The algorithm designed in this paper is used for the controller of a new industrial robot which will be equipped for the welding automatic lines of Chery Automobile Co. Ltd.

Compared to the five‐order polynomial trajectory optimization method proposed by Macfarlane and Croft, the approach described in this paper can effectively take advantage of joints maximum speed, and the calculation time of this method is shorter than conventional dynamics methods.

The characteristic of static is quite important especially for the manipulator with force feedback. This paper aims to improve the traditional static model by considering the limitations such as lacking of versatility and ignoring gravity of links. For this purpose, a new asymmetric mass distribution method on the analysis of universal “force-sensing” model has been put forward to overcome the limitations.

Through the forces and torques analysis of every link and the moving platform, the static model of 3-RUU manipulator is acquired. Then, based on the physical meaning analysis of every part in the static model of 3-RUU manipulator, a new asymmetric mass distribution method on the analysis of universal “force-sensing” model can be obtained.

The correctness of the static model of 3-RUU manipulator is verified by simulation results based on Pro/Engineer software and Adams software. Furthermore, experiment results based on a manipulator similar to the Omega.3 manipulator indicate that the universal “force-sensing” model can be applicable to the above manipulator.

A new asymmetric mass distribution method on the analysis of universal static mathematical model has been put forward. Based on physical meaning of the above method, the “force-sensing” model can be established quickly and it owns versatility, which can be applicable to the 3-RUU manipulator, the Omega.3 parallel manipulator and other similar manipulators with force feedback. In addition, it can improve the accuracy of the “force-sensing” model to a great extent.

Economic fundamentals are recognized as determining factors for housing on the city level, but the relationship between housing price and land supply has been disputed. This study aims to examine what kind of impact housing prices have on land supply and whether there is heterogeneity in different regional spaces.

This study collects the relevant data of land supply and housing prices in Nanchang from 2010 to 2018, constructs a vector autoregression (VAR) model, including one external factor and four internal factors of land supply to explore the dynamic effects and spatial heterogeneity of land supply on housing prices through regression analysis. Also, the authors use the geographic detector to analyze the spatial heterogeneity of housing prices in Nanchang.

This study found that the interaction between land supply and housing price is extremely complex because of the significant differences in the study area; the variables of land supply have both positive and negative effects on housing price, and the actual effect varies with the region; and residential land and GDP are the two major factors leading to the spatial heterogeneity in housing price.

The dynamic effects of land supply on housing price are mainly reflected in the center and edge of the city, the new development area, and the old town, which is consistent with the spatial pattern of the double core, three circles and five groups in Nanchang.

This is a novel work to analyze the dynamic effects of land supply on house prices, instead of a single amount of land supply or land prices. Furthermore, the authors also explore the spatial heterogeneity according to the regional characteristics, which is conducive to targeted policymaking.

The purpose of this study is to extract the real requirements of the owner (or users) for the construction project in the operation and maintenance stage completely and accurately and carry out the construction based on the requirements, to make the project status and operation and maintenance requirements (RO&M) consistent after delivered.

This study creatively proposes the operation and maintenance functions deployment (OMFD) under RO&M. In addition, the OPAR (naming is made up of the initials of owners, project, analysis and result) model is constructed to fully identify the requirements of both owners and projects. In this study, three typical construction projects are taken as examples to calculate the correlation strength between project characteristics (PC) and operation and maintenance requirements through the Apriori algorithm, and order parameters are obtained from the cost chain.

This study found that there are significant differences in the correlation strength between 11 types of RO&M and PC, in which the “cost of types” (TC) correlation of residential housing and factory buildings is the largest, while the largest correlation demand of commercial buildings is “safety of types” (TS) and “system” (S). Simultaneously, through the calculation of order parameters, the most influential factors on project characteristics are obtained.

This study could effectively help the owner (or users) to check whether the delivered project fully satisfy their real requirements and also extract the key technical points to realize RO&M, which can guide the accurate construction of the same type of projects.

This research establishes OPAR model to accurately identify the requirements of the project in the operation and maintenance stage and establishes the association rules between the requirements and the construction scheme, which is helpful for the project to construct under the expected requirements.