Search

Aimed to improve the stiffness identification precision of 7-degree-of-freedom (Dof) collaborative robots (Cobots), an optimal configuration selection method for elastostatic calibration of robots is researched by the influencing factor separation method. Different from previous studies, this method can deal with the influence of redundant Dof on measurement configuration selection of redundant robotic manipulators. The independent influence of each joint on the inverse condition number which is selected as the evaluation criterion is analyzed through the orthogonal design experiment and the analysis of variance, and the optimal measuring configurations of robots for stiffness identification can be selected from joint space. Based on a 7-Dof Cobot SHIR5-III, static compliance simulations are performed to identify joint stiffness of the robot. Compared to identification results by using the configurations having large, medium and small inverse condition number, the effectiveness of this optimal configuration selection method is verified and the identification accuracy can be essentially improved with configurations having a large inverse condition number.

Optimum design is proven significant for improving task performances of robotic manipulators under certain constraints. However, when it is utilized for collaborative robots (Cobots), there are still many challenges such as complex smooth surface links, time-varying kinematic configurations, computational expensiveness, and nonstructural parameter optimization. Therefore, based on orthogonal design experiment (ODE) and finite element substructure method (FESM), a multi-objective optimum design method of Cobots is proposed with the structural dimensions and parameterized joint components as the optimization variables and the natural frequency, the Cartesian stiffness, and the mass of the robot as optimization objectives. Firstly, to obtain multiple global performance indexes (GPIs) of robots in real-time and efficiently, the FESM model of Cobots is established which can preserve the accuracy of the finite element method (FEM) while ensuring the computational efficiency. Then, the gray relational analysis method (GRAM) is used to construct the multi-objective optimization function which includes the global first-order natural frequency index (GFNFI), the global elastic deformation index (GEDI), and the mass of robots. The ODE is constructed, and the structural dimensions and parameterized joint components are taken as influencing factors. According to the orthogonal array (OA), the degree of gray incidence under different levels of influencing factors is solved. And the optimal combination of influencing factor levels is obtained by range analysis (RA), which is used to guide the design of Cobots. Finally, a Cobot SHIR5-I is taken as an illustrative example to perform optimum design in this paper.

Purpose The purpose of this paper is to search the optimal arrangement scheme of random motion accuracy of joints for optimal synthesis of pose repeatability which can make robot design more reasonable and reduce the development cost of robots. Design/methodology/approach In this paper, a mathematical model of pose repeatability, which includes positioning repeatability and orientation repeatability of robots, is established. According to the ISO 9283 standard, an optimal synthesis method of pose repeatability for collaborative robots is introduced, and three optimization objective functions are proposed. The optimization model is solved by using numerical analysis software, and the optimal arrangement scheme of random motion accuracy of joints is obtained which meets the requirements of pose repeatability of robot. Findings It is found that, in three optimization objective functions, the single-objective evaluation function of maximization of joint motion error is more suitable for optimal synthesis of pose repeatability. In practice, due to the safety factor, the test results of pose repeatability are better than the results of optimal synthesis of pose repeatability. Practical implications This method makes robot design more reasonable and reduces the development cost of robots. Originality/value This work is the first time to optimize the orientation repeatability of collaborative robots. Because the pose repeatability of most robots is tested by the ISO 9283 standard, so this method which is based on this standard is more suitable for the performance requirements of robot products.

Augmented reality technology is widely used in people's life and work, especially in visual aids. How to assist users to quickly find target objects in a complex environment is one of the problems that need to be solved in the development of augmented reality technology. To solve this problem, the paper proposes an augmented reality system based on object detection neural network and a fast method to construct specific object data set. Since it is difficult for the existing object detection network to accurately detect specific objects that are not in the data set, this paper uses the self-built data set to retrain the object detection network to ensure that the object detection network can detect specific objects. Meanwhile, we calibrate the system to ensure that the bounding box in the AR glasses output from the object detection network can accurately select the specific object. This system helps users quickly find the required items from the complex real environment and enhances the interaction efficiency between users and the real world.

In order to improve the stiffness modeling accuracy, an extended stiffness modeling and identification method of a 7 degrees of freedom(Dofs) collaborative robot is introduced in this paper. Unlike the traditional stiffness model which is assumed that each actuated joint is presented by a single one-dimensional virtual spring, the compliance of links, bearings and other structural components are considered and equivalent to two virtual joints in this method. These two additional virtual joints are orthogonal to the rotation axis of actuated joints. Including the equivalent virtual joint of joint torsional stiffness, each actuated joint of the robot has three virtual joints eventually. The method extends the traditional virtual joint method(VJM) and opens new prospects in terms of the stiffness optimal synthesis. Meanwhile, the accuracy of stiffness modeling is improved. Based on a 7 Dofs collaborative robot SHIR5, the static compliance simulations are performed to identify the elastic parameters of the robot, and the results show that more precise Cartesian stiffness characteristics are obtained from the extended stiffness model. Finally, the influence of compliance of links, bearings and other structural components on the stiffness model of the robot are analyzed.

The configuration of collaborative robots is analyzed and optimized based on the Kriging model. First, through analyzing configurations of the existing collaborative robots, it can be seen that the offset is an important factor affecting the configuration, which is divided into S type and Y type by the influence on the range of motion of the joint. Then, based on the Kriging model, the multi-objective optimization function is established, which takes the length and offset of each link as parameter variables and regards the global performance index, the workspace volume index and the workspace dexterity performance index as optimization objective. And the influence of the link and offset parameters of the robot on the robot performance index is analyzed. In the end, the pareto optimal solution set and the optimization configurations are obtained using multi-objective genetic algorithm, and the performance is improved, the solution provides theoretical basis for the configuration design of collaborative robots.

In recent years, urban rail transportation develops rapidly for its advantages of high speed, safety and environmental friendliness. As the main node of urban rail transportation network, its terminal has distinct characteristics, such as large volume and high density of passenger flow. Accordingly, the main operation and management task of urban rail terminal is to improve its efficiency and safety. Based on the theory of discrete event modeling (DEM), a pedestrian model, which can evaluate and optimize passenger flow organization schemes, is developed via the complex system software AnyLogic. Taking the terminal of Shenzhen North on HuanZhong Line as an example, the method combining simulation and evaluation has been proposed and achieved, which gives a sound support for passenger flow optimization of the urban rail terminal. In addition, the spatio-temporal information of microscopic passenger flow and the maximum potential traffic benefits of promoting transit cards have been analyzed.

Nowadays, almost all the metropolises in China are facing severe urban traffic congestion. Some apps (applications) on mobile devices, such as AutoNavi Map and Baidu Map, offer free real-time traveler information and navigation service. More and more travelers are willing to utilize these mobile service to plan and optimize their personal travel activities. However, these apps have a possible influence on the urban traffic management. Although such services as the real-time navigation or traffic diversion may benefit some drivers and help to avoid congested roads, it is difficult to identify its benefits on urban traffic system level. Traffic diversion may alleviate the congestion on some roads but aggravate the traffic condition on the alternative roads. We built a microscopic traffic simulation model with complex system simulation software AnyLogic. Attempts have been made to figure out the drivers’ behavior to traffic diversion and the urban traffic network performance under real-time traffic information. In a word, this study attempts to answer: will the real-time traffic information provided by the apps brings benefits on network level or just benefits limited users? Some findings from this study may provide references for urban traffic service supply.

To improve the positioning accuracy of collaborative robots, an elastic deformation modeling method of manipulator robots is proposed in this paper. This approach is able to consider flexibility of robot modules comprehensively, and can compensate the elastic deformation caused by external wrenches and the deadweight of the robot in addition to possessing advantages of low computational complexity, easy modification as well as high real-time. Firstly, stiffness matrices of each robot module with 36 degrees of freedom (DOFs) are obtained by using the finite element analysis. Then, the kinematic model of a robot is established which is adapted to stiffness modeling of robot modules, and the force condition can be achieved by the robot statics analysis with the deadweight in order to acquire the elastic deformation of module units, which will be used to compensate the positioning error resulted from manipulator compliance. Furthermore, the elastic deformation model is built by the differential transformation method, and can be used to compensate the positioning error. Lastly, the finite element simulation is carried out, and results of the simulation show the proposed modeling method is effective.

This paper presents a complete static stiffness model of the prismatic joint of a modular reconfigurable robot based on the flnite-element-and-analytical combined method. The stiffness of the mechanical drive system was analyzed, and its tension and compression stiffness, which can be expressed by a formula, was obtained. The stiffness of the mechanical structure was extracted by employing the finite element method. The additional stiffness due to translational motion of the joint was analyzed. Then the comprehensive stiffness of the joint was obtained by combing the above stiffness parts. A simulation, which consists of four working conditions, was conducted, and the results show that the proposed method is valid.