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This paper presents a method to elaborate the selections of these parameters to achieve stable grasps. The performance of a prosthetic hand is mainly determined by its mechanical design. However, the effects of the geometric parameters of the hand configuration and the object sizes on the grasp stability are unknown.

First, the thumb functions of human hands are analyzed based on the anatomical model, and the configuration characteristics of the thumbs for typical prosthetic hands are summarized. Then a method of optimizing the thumb configuration is proposed by measuring the kinematic transmission performance of robotics. On the basis of the thumb configuration analysis, a design method of the prosthetic hand configuration is proposed based on form closure theory. The discriminant function of form closure is used to analyze and determine the hand configuration parameters.

An application of this method – the newly developed HIT V prosthetic hand – elaborates the optimization of the thumb configuration and the hand configuration, where the relation between the key hand configuration parameters and the discriminant function on condition of satisfying form closure, sustained by analytical equations and graphs, is revealed and visualized. An experimental verification shows that it is an effective method to design the prosthetic hand configuration available for grasping typical objects in our daily life.

The paper shows how to easily determine the geometric dimensions of the palm, phalanges and hand configuration, so that the desired range of object sizes can be obtained.

This paper aims to propose a novel method based on a gesture primitives analysis of human daily grasping tasks for designing dexterous hands with various grasping and in-hand manipulation abilities, which simplifies the complex and redundant humanoid five-finger hand system.

First, the authors developed the fingers and the joint configuration with a series of gesture primitives configurations and the modular virtual finger scheme, refined from the daily work gesture library by principal component analysis. Then, the authors optimized the joint degree-of-freedom configuration with the bionic design analysis of the anatomy, and the authors optimized the dexterity workspace. Furthermore, the adaptive fingertip and routing structure were designed based on the dexterous manipulation theory. Finally, the effectiveness of the design method was experimentally validated.

A novel lightweight three-finger and nine-degree-of-freedom dexterous hand with force/position perception was designed. The proposed routing structure was shown to have the capability of mapping the relationship between the joint space and actuator space. The adaptive fingertip with an embedded force sensor can effectively increase the robustness of the grasping operation. Moreover, the dexterous hand can grasp various objects in different configurations and perform in-hand manipulation dexterously.

The dexterous hand design developed in this study is less complex and performs better in dexterous manipulation than previous designs.

This study aims to introduce a multi-configuration, three-finger dexterous hand with integrated high-dimensional sensors and provides an analysis of its design, modeling and kinematics.

A mechanical design scheme of the three-finger dexterous hand with a reconfigurable palm is proposed based on the existing research on dexterous hands. The reconfigurable palm design enables the dexterous hand to achieve four grasping modes to adapt to multiple grasping tasks. To further enhance perception, two six-axis force and torque sensors are integrated into each finger. The forward and inverse kinematics equations of the dexterous hand are derived using the D-H method for kinematics modeling, thus providing a theoretical model for index analysis. The performance is evaluated using three widely applied indicators: workspace, interactivity of fingers and manipulability.

The results of kinematics analysis show that the proposed hand has excellent dexterity. Additionally, three different experiments are conducted based on the proposed hand. The performance of the dexterous hand is also verified by fingertip force, motion accuracy test, grasping and in-hand manipulation experiments based on Feix taxonomy. The results show that the dexterous hand has good grasping ability, reproducing 82% of the natural movement of the human hand in daily grasping activities and achieving in-hand manipulations such as translation and rotation.

A novel three-finger dexterous hand with multi-configuration and integrated high-dimensional sensors is proposed. It performs better than the previously designed dexterous hand in actual experiments and kinematic performance analysis.

This paper aims to present the design and experiment of a modular multisensory prosthetic hand for applications. Design and experiment of a modular multisensory hand for prosthetic applications.

This paper reveals more details focusing on the appearance, mechanism design, electrical design and control of the prosthetic hand considering anthropomorphism, dexterity, sensing and controllability. The finger is internally integrated with the actuator, the transmission mechanism, the sensors and the controller as a modular unit. Integrated with multiple sensors, the prosthetic hand can not only perceive the position, the contact force and the temperature of the environment like a human hand but also provide the foundation for the practical control.

The experiments show that the prosthetic hand can accurately control the contact force to achieve stable grasps based on the sensors feedback and a simple and effective force-tracking impedance control algorithm. In addition, the experiments based on the cosmesis validate not only the cosmesis functionality but also the control performance for a prosthesis–cosmesis system.

Because of the small size, low weight, high integration, modularity and controllability, the prosthetic hand is easily applied to upper-limb amputees. Meanwhile, the finger as a modular unit is easy to be fixed, maintained and applied to a partial upper-limb amputee.

Each modular finger of the prosthetic hand integrated with the actuator, the transmission mechanism, the sensors and the controller as a whole can independently control the position and the force. The cosmetic glove design can provide pretty appearance without compromising the control performance.

The purpose of this paper is to propose a method that calibrates the hand-eye relationship for eye-to-hand configuration and afterwards a rectification to improve the accuracy of general calibration.

The hand-eye calibration of eye-to-hand configuration is summarized as a equation AX = XB which is the same as in eye-in-hand calibration. A closed-form solution is derived. To abate the impact of noise, a rectification is conducted after the general calibration.

Simulation and actual experiments confirm that the accuracy of calibration is obviously improved.

Only a calibration plane is required for the hand-eye calibration. Taking the impact of noise into account, a rectification is carried out after the general calibration and, as a result, that the accuracy is obviously improved. The method can be applied in many actual applications.

This paper aims to present an approach for the simulation of a heterogeneous robotic cell. The simulation enables the cell’s developers to conveniently compare the performance of alternative cell configurations. The approach combines the use of multiple available simulation tools, with a custom holonic cell controller. This overcomes the limitation of currently available robot simulation packages by allowing integration of multiple simulation tools including multiple vendor simulation packages.

A feeding cell was developed as a case study representing a typical robotic application. The case study would compare two configurations of the cell, namely, eye-in-hand vision and fixed-camera vision. The authors developed the physical cell in parallel with the simulated cell to validate its performance. Then they used simulation to scale the models (by adding subsystems) and shortlist suitable cell configurations based on initial capital investment and throughput rate per unit cost. The feeding cell consisted of a six-degree of freedom industrial robot (KUKA KR16), two smart cameras (Cognex ism-1100 and DVT Legend 500), an industrial PC (Beckhoff) and custom reconfigurable singulation units.

The approach presented here allows the combination of dissimilar simulation models constructed for the above mentioned case study. Experiments showed the model developed in this approach could reasonably predict various eye-in-hand and fixed-camera systems’ performance. Combining the holonic controller with the simulation allows developers to easily compare the performance of a variety of configurations. The use of a common communication platform allowed the communication between multiple simulation packages, allowing multi-vendor simulation, thereby overcoming current limitation in simulation software.

The case study developed here is considered a typical feeding and assembly application. This is however very different from other robotic applications which should be explored in separate case studies. Simulation packages with the same communication interface as the physical resource can be integrated. If the communication interface is not available, other means of simulation can be used. The case study findings are limited to the specific products being used and their simulation packages. However, these are indicative of typical industry technologies available. Only real-time simulations were considered.

This simulation-based approach allows designers to quickly quantify the performance of alternative system configurations (eye-in-hand or fixed camera in this case) and scale, thereby enabling them to better optimize robotic cell designs. In addition, the holonic control system’s modular control interface allows for the development of the higher-level controller without hardware and easy replacement of the lower level components with other hardware or simulation models.

The combination of a holonic control system with a simulation to replace hardware is shown to be a useful tool. The inherent modularity of holonic control systems allows that multiple simulation components be connected, thereby overcoming the limitation of vendor-specific simulation packages.

The purpose of this paper is to design a multifingered dexterous hand grasping planning method that can efficiently perform grasping tasks on multiple dexterous hand platforms.

The grasping process is divided into two stages: offline and online. In the offline stage, the grasping solution form is improved based on the forward kinematic model of the dexterous hand. A comprehensive evaluation method of grasping quality is designed to obtain the optimal grasping solution offline data set. In the online stage, a safe and efficient selection strategy of the optimal grasping solution is proposed, which can quickly obtain the optimal grasping solution without collision.

The experiments verified that the method can be applied to different multifingered dexterous hands, and the average grasping success rate for objects with different structures is 91.7%, indicating a good grasping effect.

Using a forward kinematic model to generate initial grasping points can improve the generality of grasping planning methods and the quality of initial grasping solutions. The offline data set of optimized grasping solutions can be generated faster by the comprehensive evaluation method of grasping quality. Through the simple and fast obstacle avoidance strategy, the safe optimal grasping solution can be quickly obtained when performing a grasping task. The proposed method can be applied to automatic assembly scenarios where the end effector is a multifingered dexterous hand, which provides a technical solution for the promotion of multifingered dexterous hands in industrial scenarios.

The clustering of objects in a layered object storage system is by common consent an exceedingly difficult problem. Studies the performance of three heuristic placement algorithms. A series of eight reasonably realistic case studies were used as a benchmark battery, and several hundred experiments were carried out to evaluate results of using the algorithms. Presents the results and the insights gained from the study.

This paper aims to present an integrative review of the research studies on nursing unit layouts.

Studies selected for review were published between 1956 and 2014. For the purpose of this review, a framework for integrative review was developed using research orientations. The three primary dimensions – technical, psychological and social – of the designed environment and various combinations of these dimensions were used to define the research orientations of these studies.

Of all the publications reviewed for the paper, 21 presented technical orientations, 16 psychological orientations, 3 social orientations, 20 psychotechnical orientations, 10 sociotechnical orientations, 2 psychosocial orientations and 13 presented psychosociotechnical orientations. With only a few exceptions, several issues related to nursing unit layouts were investigated no more than one time in any one category of research orientations. Several other seemingly important issues including patient and family behavior and perception, health outcomes and social and psychosocial factors in relation to unit layouts have not been studied adequately.

Future studies on nursing unit layouts will need to focus on patient and family behavior and perception, health outcomes and social and psychosocial factors in different units. They will also need to focus on developing theories concerning the effects of layouts on the technical, psychological and social dimensions of nursing units.

Despite a long history of research on nursing unit layouts, an integrative review of these studies is still missing in the literature. This review fills in the gap using a novel framework for integrative review developed based on research orientations.

In this paper, a biocybernetic method to learn hand grasping posture definition with few knowledge about the task is proposed. The developed model is composed of two stages. The first is dedicated to the fingers inverse kinematics learning in order to locally define a single finger posture given its desired fingertip position. This motor function is fulfilled by a modular neural network architecture that tackles the discontinuity problem of inverse kinematics function (called Fingers Configuration Neural Network (FCNN)). Following the concept of direct associative learning, a second neural model is used to search the space of hand configuration and optimize it according to an evaluative function based on the results of the FCNN. Simulation results show good learning of grasping posture determination of various object types, with different numbers of fingers involved and different contact configurations.