具有震颤抑制的微创机器人主从控制系统设计

详述了一种用于抑制微创手术机器人震颤现象的主从控制系统，提出了针对人手生理震颤的新型零相位滤波方法及针对从操作臂关节“粘滑行为”的前馈补偿PD伺服算法。新型零相位滤波避免了传统低通滤波器容易造成延时和传统零相位滤波无法在线使用的缺点，前馈补偿PD伺服算法通过摩擦补偿克服了非线性摩擦对从操作臂运动造成的影响。最后，对系统进行仿真及实验，结果表明该方法能有效地抑制机器人手术工具末端的震颤现象。     

CroMatcher: An ontology matching system based on automated weighted aggregation and iterative final alignment

In order to perform ontology matching with high accuracy, while at the same time retaining applicability to most diverse input ontologies, the matching process generally incorporates multiple methods. Each of these methods is aimed at a particular ontology component, such as annotations, structure, properties or instances. Adequately combining these methods is one of the greatest challenges in designing an ontology matching system. In a parallel composition of basic matchers, the ability to dynamically set the weights of the basic matchers in the final output, thus making the weights optimal for the given input, is the key breakthrough for obtaining first-rate matching performance. In this paper we present CroMatcher, an ontology matching system, introducing several novelties to the automated weight calculation process. We apply substitute values for matchers that are inapplicable for the particular case and use thresholds to eliminate low-probability alignment candidates. We compare the alignments produced by the matchers and give less weight to the matchers producing mutually similar alignments, whereas more weight is given to those matchers whose alignment is distinct and rather unique. We also present a new, iterative method for producing one-to-one final alignment of ontology structures, which is a significant enhancement of similar non-iterative methods proposed in the literature. CroMatcher has been evaluated against other state-of-the-art matching systems at the OAEI evaluation contest. In a large number of test cases it achieved the highest score, which puts it among the state-of-the-art leaders.     

High-velocity walk-through programming for industrial applications

Traditionally, industrial robots are programmed by highly specialized workers that either directly write code in platform-specific languages, or use dedicated hardware (teach-pendant) to move the robot through the desired via-points. Unsurprisingly, the inherently complex and time-consuming nature of this task is one of the factors that are still preventing industrial manipulators from being massively adopted by companies that require a high degree of flexibility in order to cope with limited production volumes and rapidly changing product requirements. In this context, the introduction of sensor-based walk-through programming approaches represents the ideal solution as far as the need to reduce programming complexity and time is concerned. Nevertheless, the main shortcomings of these solutions typically consist in limited reachable velocities during the programming phase due to safety constraints and in relying on open robot controllers. To this regard, this paper proposes a control architecture for walk-through programming of industrial manipulators specifically designed in order to (i) reach high velocities while guaranteeing the operator’s safety; (ii) allow straightforward integration with a generic closed robotic controller. The proposed solution is extensively validated on an industrial manipulator.     

Human–robot interaction in industrial collaborative robotics: a literature review of the decade 2008–2017

ABSTRACT

Currently, a large number of industrial robots have been deployed to replace or assist humans to perform various repetitive and dangerous manufacturing tasks. However, based on current technological capabilities, such robotics field is rapidly evolving so that humans are not only sharing the same workspace with robots, but also are using robots as useful assistants. Consequently, due to this new type of emerging robotic systems, industrial collaborative robots or cobots, human and robot co-workers have been able to work side-by-side as collaborators to accomplish tasks in industrial environments. Therefore, new human–robot interaction systems have been developed for such systems to be able to utilize the capabilities of both humans and robots. Accordingly, this article presents a literature review of major recent works on human–robot interactions in industrial collaborative robots, conducted during the last decade (between 2008 and 2017). Additionally, the article proposes a tentative classification of the content of these works into several categories and sub-categories. Finally, this paper addresses some challenges of industrial collaborative robotics and explores future research issues.     

Parallel preparation and properties investigation on Li2O-Nb2O5-TiO2 microwave dielectric ceramics

A parallel preparation method was developed using dry powders as starting materials to synthesize multi-compositional microwave dielectric ceramics. The Li₂O-Nb₂O₅-TiO₂ ternary system was investigated as a model material. The validity of the parallel ceramic preparation process was confirmed by synthesizing a group of LiNb_0.6Ti_0.5O₃ ceramics in parallel, which showed the same crystalline structure and close dielectric properties. The ceramic libraries with M-phase-rich samples and Li₂TiO₃-rich samples were prepared using the parallel process, and the microwave dielectric properties and crystal phases were investigated systematically. An excellent microwave ceramic with a composition of 0.55Li₂O-0.05Nb₂O₅-0.40TiO₂ was obtained, which has a dielectric constant of 18.4 and a high quality value (Q × f) of 79000 GHz. This parallel process can be applied extensively to explore a variety of bulk ceramic libraries for discovering new functional materials with high performances.     

Rule-based meta-heuristics for integrated scheduling of unrelated parallel machines,batches, and heterogeneous delivery trucks

In this article, we deal with an integrated scheduling for unrelated parallel machines, batches, and heterogeneous delivery trucks. In a manufacturing plant, jobs ordered by customers are manufactured by one of several unrelated parallel machines. Then, they are grouped and delivered to the respective customers by heterogeneous trucks with different capacities and travel times. The objective of the problem is to simultaneously determine the machine schedule, batching, and truck-delivery schedule to minimize the make span of the entire process. To solve this problem, we derive a mathematical model to obtain the optimal solution, and we propose rule-based meta-heuristics using single-stage GA framework. Through randomly generated instance examples, the performances of the proposed meta-heuristics are compared.     

Self-calibration of stationary non-rotating zooming cameras

This paper proposes a new method for self-calibrating a set of stationary non-rotating zooming cameras. This is a realistic configuration, usually encountered in surveillance systems, in which each zooming camera is physically attached to a static structure (wall, ceiling, robot, or tripod). In particular, a linear, yet effective method to recover the affine structure of the observed scene from two or more such stationary zooming cameras is presented. The proposed method solely relies on point correspondences across images and no knowledge about the scene is required. Our method exploits the mostly translational displacement of the so-called principal plane of each zooming camera to estimate the location of the plane at infinity. The principal plane of a camera, at any given setting of its zoom, is encoded in its corresponding perspective projection matrix from which it can be easily extracted. As a displacement of the principal plane of a camera under the effect of zooming allows the identification of a pair of parallel planes, each zooming camera can be used to locate a line on the plane at infinity. Hence, two or more such zooming cameras in general positions allow the obtainment of an estimate of the plane at infinity making it possible, under the assumption of zero-skew and/or known aspect ratio, to linearly calculate the camera's parameters. Finally, the parameters of the camera and the coordinates of the plane at infinity are refined through a nonlinear least-squares optimization procedure. The results of our extensive experiments using both simulated and real data are also reported in this paper.     

Large-scale parallel lattice Boltzmann–cellular automaton model of two-dimensional dendritic growth

An extremely scalable lattice Boltzmann (LB)–cellular automaton (CA) model for simulations of two-dimensional (2D) dendritic solidification under forced convection is presented. The model incorporates effects of phase change, solute diffusion, melt convection, and heat transport. The LB model represents the diffusion, convection, and heat transfer phenomena. The dendrite growth is driven by a difference between actual and equilibrium liquid composition at the solid–liquid interface. The CA technique is deployed to track the new interface cells. The computer program was parallelized using the Message Passing Interface (MPI) technique. Parallel scaling of the algorithm was studied and major scalability bottlenecks were identified. Efficiency loss attributable to the high memory bandwidth requirement of the algorithm was observed when using multiple cores per processor. Parallel writing of the output variables of interest was implemented in the binary Hierarchical Data Format 5 (HDF5) to improve the output performance, and to simplify visualization. Calculations were carried out in single precision arithmetic without significant loss in accuracy, resulting in 50% reduction of memory and computational time requirements. The presented solidification model shows a very good scalability up to centimeter size domains, including more than ten million of dendrites.     

基于RobotStudio的芯片智能分拣生产线设计

为了缩短芯片智能分拣生产线开发周期,利用虚拟仿真技术在RobotStudio软件中搭建仿真工作站;该工作站以ABB IRB360并联工业机器人为控制核心,利用Solidworks建模软件完成相关模型建立,利用RobotStudio软件的Smart组件、机械装置等功能实现芯片下料、芯片传输、相机检测等过程,设计工业机器人的路径和程序完成分拣工作;最后将仿真工作站的代码直接下载至现场工业机器人,并根据仿真节拍调节现场各模块工作速度,实现芯片的智能分拣;实验结果表明,工业机器人能够根据相机的引导正确且高效地分拣芯片.