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The measurement of aircraft barycenter is a verification of theoretical barycenter and is an important step of aircraft development. In the traditional measurement method of aircraft barycenter, the posture of the aircraft needs to be adjusted manually and is measured by optical instruments. The efficiency of posture adjustment depends on the proficiency of workers, and the accuracy of measurement is not high. In view of these problems of the current barycenter measurement method, this paper aims to propose an aircraft barycenter measurement method based on multi-posture.

In this method, the numerical control locator is used as a supporting part to fix and adjust the aircraft, and the calculation model of aircraft barycenter is established according to the principle of rigid body rotation and the principle of moment balance. Then, the influence of the main error sources on the measurement accuracy of aircraft barycenter is analyzed by Monte Carlo simulation, and the measurement accuracy is compared with that of the barycenter measurement method based on horizontal posture. Finally, the experiment platform of barycenter measurement was built in the laboratory and the experiments were carried out.

The experimental results show that the barycenter measurement method proposed in this paper has obvious advantages in measurement accuracy and efficiency compared with the traditional method.

This method can be used to measure the barycenter of different types of aircraft quickly and automatically.

This paper aims to propose a measurement principle and a calibration method of measurement system integrated with serial robot and 3D camera to identify its parameters conveniently and achieve high measurement accuracy.

A stiffness and kinematic measurement principle of the integrated system is proposed, which considers the influence of robot weight and load weight on measurement accuracy. Then an error model is derived based on the principle that the coordinate of sphere center is invariant, which can simultaneously identify the parameters of joint stiffness, kinematic and hand-eye relationship. Further, considering the errors of the parameters to be calibrated and the measurement error of 3D camera, a method to generate calibration observation data is proposed to validate both calibration accuracy and parameter identification accuracy of calibration method.

Comparative simulations and experiments of conventional kinematic calibration method and the stiffness and kinematic calibration method proposed in this paper are conducted. The results of the simulations show that the proposed method is more accurate, and the identified values of angle parameters in modified Denavit and Hartenberg model are closer to their real values. Compared with the conventional calibration method in experiments, the proposed method decreases the maximum and mean errors by 19.9% and 13.4%, respectively.

A new measurement principle and a novel calibration method are proposed. The proposed method can simultaneously identify joint stiffness, kinematic and hand-eye parameters and obtain not only higher measurement accuracy but also higher parameter identification accuracy, which is suitable for on-site calibration.

This paper sets out to propose a wafer prealigner based on multi‐sensor integration and an effective prealignment method implemented on it.

The wafer and notch eccentricities, on which wafer prealignment is based, are calculated with the peripheral data of the wafer detected by a laser displacement sensor and a transmission laser sensor by means of barycenter acquiring algorithm in a one‐particle system.

The center and notch prealignment precisions of the system are, respectively, ±1.5 μm and ±30 μrad. Experimentation has proved the validity and effectiveness of the system.

The wafer prealigner is a subsystem of the lithography in the semiconductor industry. The prealignment algorithm can be implemented in any object with random figures.

The periphery of the wafer is detected by a high‐precision laser displacement sensor and a low‐cost transmission laser sensor instead of a CCD linear sensor used by traditional wafer prealigners, which saves the space occupation of the structure and enhances the systematic prealignment precision. Using barycenter acquiring algorithm in a one‐particle system to calculate the wafer and notch eccentricities is effective and valid.

The purpose of this paper is to study the adaptability of the tracked robot in complex working environment. It proposes an angle-changeable tracked robot with human–robot interaction in unstructured environment. The study aims to present the mechanical structure and human–robot interaction control system of the tracked robot and analyze the static stability of the robot working in three terrains, i.e. rugged terrain, sloped terrain and stairs.

The paper presents the mechanical structure and human–robot interaction control system of the tracked robot. To prevent the detachment of the tracks during obstacle navigation, a new type of passively adaptive device based on the relationship between the track’s variable angle and the forces is presented. Then three types of rough terrain are chosen to analyze the static stability of the tracked robot, i.e. rugged terrain, sloped terrain and stairs.

This paper provides the design method of the tracked robot. Owing to its appropriate dimensions, good mass distribution and limited velocity, the tracked robot remains stable on the complex terrains. The experimental results verify the effectiveness of the design method.

The theoretical analysis of this paper provides basic reference for the structural design of tracked robots.

The fast and easy generation of personalized mannequin is the premise for the accurate 3D measurement for the customers in an electronic made to measure (e_MTM) system. The purpose of this paper is to attempt to propose a new virtual human mannequin modeling technique to meet this requirement.

The customized human mannequin is constructed by assemblage of the body parts. The body parts including bust, waist and hip segments are achieved by modification of the standard body section templates, while the silhouette obtained from the front and side photos are used to confine the distortion of the parts.

The main findings are the section template base and assemblage method for mannequin modeling.

The proposed method can free the burden of high cost and inconvenience of 3D scanner in the measurement process of e_MTM system, and in the mean time without loss of measurement accuracy.

Aiming at the problems of geometric precision misalignment and unconsidered physical constraints between large components during the measurement-assisted assembly, a self-adaptive alignment strategy based on the dynamic compliance center (DCC) is proposed in this paper, using force information to guide alignment compliantly.

First, the self-adaptive alignment process of large components is described, and its geometrical and mechanical characteristics are analyzed based on six-dimensional force/torque (F/T). The setting method of DCC is studied and the areas of DCC are given. Second, the self-adaptive alignment platform of large components driven by the measured six-dimensional F/T is constructed. Based on this platform, the key supporting technologies, including principle of self-adaptive alignment, coordinate transfer, calculation of six-dimensional F/T and alignment process control, are illustrated.

Using the presented strategy, the position and orientation of large component is adjusted adaptively responding to measured six-dimensional F/T and the changes of contact states are consistent with the strategy. Through the setting of DCC, alignment process runs smoothly without jamming.

This strategy is applied to the alignment experiment of large components muff coupling. The experimental results show that the proposed alignment strategy is correct and effective and meets the real-time requirement.

This paper proposed a novel way to apply force information in large component self-adaptive alignment, and the setting method of DCC was presented to make the alignment process more feasible.

This paper aims to present a procedure to change the orientation of a grasped object using dexterous manipulation. The manipulation is controlled by teleoperation in a very simple way, with the commands introduced by an operator using a keyboard.

The paper shows a teleoperation scheme, hand kinematics and a manipulation strategy to manipulate different objects using the Schunk Dexterous Hand (SDH2). A state machine is used to model the teleoperation actions and the system states. A virtual link is used to include the contact point on the hand kinematics of the SDH2.

Experiments were conducted to evaluate the proposed approach with different objects, varying the initial grasp configuration and the sequence of actions commanded by the operator.

The proposed approach uses a shared telemanipulation schema to perform dexterous manipulation; in this schema, the operator sends high-level commands and a local system uses this information, jointly with tactile measurements and the current status of the system, to generate proper setpoints for the low-level control of the fingers, which may be a commercial close one. The main contribution of this work is the mentioned local system, simple enough for practical applications and robust enough to avoid object falls.

Since 2012, with the Growth Decree 2.0, the Italian Government has been engaged in promoting the establishment and the growth of new innovative startups with a high technological value. The general objective of the policy is to promote sustainable growth, technological advancement and innovation. In the Decree framework, startups have to own an innovative character that is identified by at least one of the following three criteria: investments in research and development, qualified workforce, holding patents or registered software. Such three characteristics can be considered as innovation inputs able to create the conditions for a competitive advantage and greater economic performance. The research objective is to analyze how innovation inputs in innovative startups affect their economic performance. Each input factor can have a different impact on the company profitability. To this end, we apply the methodology SMAA for strategic management analysis and assessment (or SMAA-S) to detect the relation between innovation and profitability in Italian startups.

This paper aims to provide a focused review on the geometrical designs for performance enhancement of piezoresistive microaccelerometers.

By analyzing working principle and conventional geometries, the improved research proposals are sorted into three groups in terms of their anticipated objectives, including sensitivity, resonant frequency and cross-axis sensitivity. Accessible methods are outlined and their merits and demerits are described.

Novel geometries obviously enhance the performance of accelerometers, and the efficacy can be further elevated by newer materials and fabrication processes.

This paper mainly focused on the improved geometrical designs for sensitivity, resonant frequency and cross-axis sensitivity. Other performance parameters or design schemes are not included in this paper.

This paper generalizes the available geometries and methods for the enhancement of sensitivity, resonant frequency and cross-axis sensitivity in piezoresistive accelerometers design.

The aim of this paper is to propose a grasping method based on intelligent perception for implementing a grasp task with human conduct.

First, the authors leverage Kinect to collect the environment information including both image and voice. The target object is located and segmented by gesture recognition and speech analysis and finally grasped through path teaching. To obtain the posture of the human gesture accurately, the authors use the Kalman filtering (KF) algorithm to calibrate the posture use the Gaussian mixture model (GMM) for human motion modeling, and then use Gaussian mixed regression (GMR) to predict human motion posture.

In the point-cloud information, many of which are useless, the authors combined human’s gesture to remove irrelevant objects in the environment as much as possible, which can help to reduce the computation while dividing and recognizing objects; at the same time to reduce the computation, the authors used the sampling algorithm based on the voxel grid.

The authors used the down-sampling algorithm, kd-tree algorithm and viewpoint feature histogram algorithm to remove the impact of unrelated objects and to get a better grasp of the state.