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The structural adaptive ability of the soft robot is fully demonstrated in the grasping task of the soft hand. A soft hand can easily realize the envelope operation of the object without planning. With the continuous development of robot applications, researchers are no longer satisfied with the ability of the soft hand to grasp. The purpose of this paper is to perceive the object’s shape while grasping to provide a decision-making basis for more intelligent robot applications.

This paper proposes a dual-signal comparison method to obtain the fingertip position. The dual signal includes the displacement calculated by the static model without considering the external load change and the displacement calculated by the bending sensor. The dual-signal comparison method can use the obvious change trend difference between the above two signals in the hover and contact states to identify the touch position. The authors make the soft hand scan around the object through touch operation to detect the object’s shape, and the tracks of every touch fingertip position can envelop the object’s shape.

The experimental results show that the dual-signal comparison method can accurately identify the contact moment of soft fingers. This detection method makes the soft hand develop the shape detection ability. The soft hand in the experiment can perceive squares, circles and a few other complex shapes.

The dual-signal comparison method proposed in this paper can detect a touch action by using the signal change trend when the working condition suddenly changes with the rough robotic model and sensing, thus improving the utilization value of the measured signal. The problems of large model errors and inaccurate sensors also negatively impact the use of other soft robots. It is generally difficult to achieve good results by directly using these models and sensors with the thinking of rigid robot analysis. The dual-signal comparison method in this paper can provide some reference for this aspect.

In this paper the capital asset pricing model is extended to include the local property tax, the corporate income tax, and a borrowing rate that increases with the percentage of property value borrowed. The optimal percentage to borrow increases with the risk‐free interest rate and the corporate tax rate, decreases with an exogenous increase in the borrowing rate, and does not depend upon the property tax rate. REITs and limited partnerships have no incentive to borrow in this model, so other motives for borrowing must be posited.

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.

Companies are increasingly bringing personnel together into teams from different countries, physically and/or electronically, to develop products for multiple or worldwide markets. Called global new product teams (GNPTs), these groups face significant challenges, including cultural diversity. Differing cultural values can lead to conflict, misunderstanding, and inefficient work styles on the one hand, and strong idea generation and creative problem solving on the other. A study was conducted to identify team compositions that would optimize the effects of national culture so that product development outcomes are favorable. This began by developing a theoretical framework describing the impact of national culture on product development tasks. The framework was then translated into several mathematical models using analytical derivations and comparative statics. The models identify the levels and variances of culture values that maximize product development success by simultaneously considering four relevant dimensions of GNPT performance. Next, the utility of these models was tested by means of numerical simulations for a range of team scenarios. Concludes by drawing implications of the findings for managers and researchers.

To identify the dexterity of spacesuit gloves, they need to undergo bending tests in the development process. The ideal way is to place a humanoid robotic hand into the spacesuit glove, mimicking the motions of a human hand and measuring the bending angle/force of the spacesuit glove. However, traditional robotic hands are too large to enter the narrow inner space of the spacesuit glove and perform measurements. This paper aims to design a humanoid robot hand that can wear spacesuit gloves and perform measurements.

The proposed humanoid robotic hand is composed of five modular fingers and a parallel wrist driven by electrical linear motors. The fingers and wrist can be delivered into the spacesuit glove separately and then assembled inside. A mathematical model of the robotic hand is formulated by using the geometric constraints and principle of virtual work to analyze the kinematics and statics of the robotic hand. This model allows for estimating the bending angle and output force/torque of the robotic hand through the displacement and force of the linear motors.

A prototype of the robotic hand, as well as its testing benches, was constructed to validate the presented methods. The experimental results show that the whole robotic hand can be transported to and assembled in a spacesuit glove to measure the motion characteristics of the glove.

The proposed humanoid robotic hand provides a new method for wearing and measuring the spacesuit glove. It can also be used to other gloves for special protective suits that have highly restricted internal space.

This paper presents a new method for deploying RoboCrane‐type cable robots, without the need for fixed rigid cable support points. That is, the system provides its own deployable mobile overhead support points.

This paper presents a new RoboCrane support concept based on rigid members, cable actuation, and cable suspension. It is self‐contained and provides mobility for the required six overhead cable connections, thus extending the workspace of the existing RoboCrane. The paper presents the RoboCrane support concept overview, followed by kinematics and statics analysis, plus a case study of a specific design.

Design for kinematic horizontality, workspace, and statics are competing so the designer must make tradeoffs for the best system performance according to specific design needs.

Since the support system plus RoboCrane are both cable‐suspended robots, there are limitations in the pseudostatic workspace, i.e. since the cables can only exert tension and cannot push, the motion range is limited.

Specific system design and deployment is still remaining work – practical issues such as outriggers for moment and tipping resistance, easy portability, control of the mast from the ground, and safety must be solved in the future.

Enables RoboCrane applications in many more arenas, such as automated construction, where rigid overhead cable support points are simply unavailable.

Mechanoreception is crucial for robotic planning and control applications, and for robotic fingers, mechanoreception is generally obtained through tactile sensors. As a new type of robotic finger, the soft finger also requires mechanoreception, like contact force and object stiffness. Unlike rigid fingers, soft fingers have elastic structures, meaning there is a connection between force and deformation of the soft fingers. It allows soft fingers to achieve mechanoreception without using tactile sensors. This study aims to provide a mechanoreception sensing scheme of the soft finger without any tactile sensors.

This research uses bending sensors to measure the actual bending state under force and calculates the virtual bending state under assumed no-load conditions using pressure sensors and statics model. The difference between the virtual and actual finger states is the finger deformation under load, and its product with the finger stiffness can be used to calculate the contact force. There are distinctions between the virtual and actual finger state change rates in the pressing process. The difference caused by the stiffness of different objects is different, which can be used to identify the object stiffness.

Contact force perception can achieve a detection accuracy of 0.117 N root mean square error within the range of 0–6 N contact force. The contact object stiffness perception has a detection average deviation of about 15%, and the detection standard deviation is 10% for low-stiffness objects and 20% for high-stiffness objects. It performs better at detecting the stiffness of low-stiffness objects, which is consistent with the sensory ability of human fingers.

This paper proposes a universal mechanoreception method for soft fingers that only uses indispensable bending and pressure sensors without tactile sensors. It helps to reduce the hardware complexity of soft robots. Meanwhile, the soft finger no longer needs to deploy the tactile sensor at the fingertip, which can benefit the optimization design of the fingertip structure without considering the complex sensor installation. On the other hand, this approach is no longer confined to adding components needed. It can fully use the soft robot body’s physical elasticity to convert sensor signals. Essentially, It treats the soft actuators as soft sensors.

This paper aims to investigate empirically the findings of an analytical impure public good model. The impure public good model described in this study allows for the application of different technologies generating public and private characteristics. The influence of the individual technologies on the total level of (impure) public good provision is of main concern in this study.

After the illustration of the impure public good model, the analytical results are compared to the results of a numerical approach based on climate policy in Germany.

The study shows that comparative static analyses do not always generate clear results. Therefore, the numerical approach is helpful to derive unambiguous results. The paper finds that technologies which exclusively generate private characteristics may have significant effects on total impure public good provision, since they may replace the private characteristics of the impure public good.

This paper provides useful information on the influence of the individual technologies on the total level of (impure) public good provision.

A numerical model of deformable block systems that gives a unique solution for large displacement, large deformation and failure computations is presented. The forces acting on each block, from external loading or contact with other blocks, satisfy the equilibrium equations. Equilibrium is also achieved between external forces and the block stresses. Furthermore, the analysis fulfills constraints of no tension between blocks and no penetration of one block into another. Also, Coloumb's law is fulfilled at all contact positions for both static and dynamic computations. The program ready algorithms with brief derivations are stated in this paper.