21 resultados para parallel kinematic machine

em Deakin Research Online - Australia


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One well acknowledged drawback of traditional parallel kinematic machines (PKMs) is that the ratio of accessible workspace to robot footprint is small for these structures. This is most likely a contributing reason why relatively few PKMs are used in industry today. The SCARA-Tau structure is a parallel robot concept designed with the explicit goal of overcoming this limitation and developing a PKM with a workspace similar to that of a serial type robot of the same size. This paper shows for the first time how a proposed variant of the SCARA-Tau PKM can improve the usability of this robot concept further by significantly reducing the dependence between tool platform position and orientation of the original concept. The inverse kinematics of the proposed variant is derived and a comparison is made between this structure and the original SCARA-Tau concept, both with respect to platform orientation changes and workspace.

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A novel 6-DOF parallel kinematic manipulator named the Octahedral Hexarot is presented and analyzed. It is shown that this manipulator has the important benefits of combining a large positional workspace in relation to its footprint with a sizable range of platform rotations. These features are obtained by combining a rotation-symmetric actuating arm system with links in an octahedral-like configuration. Thus the manipulator consists of a central cylindrical column with six actuated rotating upper arms that can rotate indefinitely around the central column. Each upper arm is connected to a manipulated platform by one 5-DOF lower arm link. The link arrangement of the Octahedral Hexarot is inspired by the original Gough platform. The manipulated platform is an equilateral triangle and the joint positions on the upper arms approximately form an equilateral triangle. A task dependent optimization procedure for the structural parameters is proposed and the workspace of the resulting manipulator is analyzed in depth.

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Our present research focuses on kinematic and dynamic modeling of a 3-DOF robotic cutting head for the next generation of CNC machines. The robotic cutting head is one kind of parallel manipulator of 3-PUU type, which has a high flexibility of motion in three-dimensional space. The parallel manipulator consists of three linear servomotors, which drive three connecting rods independently according to the cutting strategy. Being a parallel manipulator, the robotic cutting head has higher stiffness and position accuracy; consequently, higher velocities and accelerations can be achieved. A very suitable application of this mechanism is as a cutting head of a precision machine tool for three-dimensional cutting problems.

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The paper describes some details of the mechanical and kinematics design of a five-axis mechanism. The design has been utilized to physically realize an industrial-scale five-axis milling machine that can carry a three KW spindle. However, the mechanism could be utilized in other material processing and factory automation applications. The mechanism has five rectilinear joints/axes. Two of these axes are arranged traditionally, i.e. in series, and the other three axes utilize the concept of parallel kinematics. This combination results in a design that allows three translational and two rotational two-mode degrees of freedom (DOFs). The design provides speed, accuracy and cost advantages over traditional five-axis machines. All axes are actuated using linear motors.

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The paper introduces a family of three-DOFs translational-rotational Parallel-Kinematics Mechanisms (PKMs) as well as the mobility analysis of such family using Lie-group theory. Each member of this family has two-rotational one-translational DOFs. A novel mechanism is presented and analyzed as a representative of that family. The use and the practical value of that modular mechanism are emphasized.


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The aim of the work was to reduce the cost and improve the performance of five-axis machines. The main performance criteria were motion cycle-time and positioning accuracy/precision. A novel machine that utilizes the concept of parallel-kinematics and linear motor technology is proposed, designed, built and controlled for this sake.

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Parallel mechanisms possess several advantages such as the possibilities for high acceleration and high accuracy positioning of the end effector. However, most of the proposed parallel manipulators suffer from a limited workspace. In this paper, a novel 6-DOF parallel manipulator with coaxial actuated arms is introduced. Since parallel mechanisms have more workspace limitations compared to that of serial mechanisms, determination of the workspace in parallel manipulators is of the utmost importance. For finding position, angular velocity, and acceleration, in this paper, inverse and forward kinematics of the mechanism are studied and after presenting the workspace limitations, workspace analysis of the hexarot manipulator is performed by using MATLAB software. Next, using the obtained cloud of points from simulation, the overall borders of the workspace are illustrated. Finally, it is shown that this manipulator has the important benefits of combining a large positional workspace in relation to its footprint with a sizable range of platform rotations.

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Anti-spam technology is developing rapidly in recent years. With the emerging applications of machine learning in diverse fields, researchers as well as manufacturers around the world have attempted a large number of related algorithms to prevent spam. In this paper, we designed an effective anti-spam protection system, SpamCooling, based on the mechanism of active learning and parallel heterogeneous ensemble learning techniques. The system adopts a batch method to filter spam and can be easily incorporated with existing mail clients (MUA). It can actively obtain user feedbacks for providing users with personalized spam filtering experiences. The parallel heterogeneous ensemble method can help system achieve high spam detection rate as well as low ham misclassification rate.

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A family of planar parallel manipulators is investigated and some novel members are proposed. The common feature of the studied manipulators is that the rotation axes of the actuated arms coincide. This feature makes it possible to rotate the whole arm system an infinite number of revolutions around the center of the manipulator. The result is a large workspace in relation to the footprint. Both 2- and 3-DOF variants are presented and the suitability of this family of manipulators for kinematic analysis is demonstrated. Thus, different methods to find optimal manipulability with respect to platform positioning and rotation have been analyzed.

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This chapter addresses the exploitation of a supervised machine learning technique to automatically induce Arabic-to-English transfer rules from chunks of parallel aligned linguistic resources. The induced structural transfer rules encode the linguistic translation knowledge for converting an Arabic syntactic structure into a target English syntactic structure. These rules are going to be an integral part of an Arabic-English transfer-based machine translation. Nevertheless, a novel morphological rule induction method is employed for learning Arabic morphological rules that are applied in our Arabic morphological analyzer. To demonstrate the capability of the automated rule induction technique, we conducted rule-based translation experiments that use induced rules from a relatively small data set. The translation quality of the hybrid translation experiments achieved good results in terms of WER.

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This paper analyses the kinematics of a special 6-DOF parallel micro-manipulator with offset RR-joint configuration. Kinematics equations are derived and numerical methodologies to solve the inverse and forward kinematics are presented. The inverse and forward kinematics of such robots compared with those of 6-UCU parallel robots are more complicated due to the existence of offsets between joints of RR-pairs. The characteristics of RR-pairs used in this manipulator are investigated and kinematics constraints of these offset U-joints are mathematically explained in order to find the best initial guesses for the numerical solution. Both inverse and forward kinematics of the case study 6-DOF parallel micro-manipulator are modelled and computational analyses are performed to numerically verify accuracy and effectiveness of the proposed methodologies.

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A methodology for the numerical solution of the forward kinematics problem of 6-RRCRR parallel manipulators with orthogonal non-intersecting RR-joint configuration is presented in this article. The inverse and forward kinematics solutions of such robots compared with that of parallel robots with orthogonal intersecting RR-joint or universal joint configurations are much more complicated due to the existence of dependent joint variables. The constraints of RR-joints are analysed and the numerical algorithm for the forward kinematics solution is assessed. Numerical results for the solution of the forward kinematics of 6-RRCRR parallel robot under study are provided to confirm the accuracy and efficiency of the procedure.

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Monotonicity preserving interpolation and approximation have received substantial attention in the last thirty years because of their numerous applications in computer aided-design, statistics, and machine learning [9, 10, 19]. Constrained splines are particularly popular because of their flexibility in modeling different geometrical shapes, sound theoretical properties, and availability of numerically stable algorithms [9,10,26]. In this work we examine parallelization and adaptation for GPUs of a few algorithms of monotone spline interpolation and data smoothing, which arose in the context of estimating probability distributions.

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In modern computing paradigms, most computing systems, e.g., cluster computing, grid computing, cloud computing, the Internet, telecommunication networks, Cyber- Physical Systems (CPS), and Machine-to-Machine communication networks (M2M), are parallel and distributed systems. While providing improved expandability, manageability, efficiency, and reliability, parallel and distributed systems increase their security weaknesses to an unprecedented scale. As the system devices are widely connected, their vulnerabilities are shared by the entire system. Because tasks are allocated to, and information is exchanged among the system devices that may belong to different users, trust, security, and privacy issues have yet to be resolved. This special issue of the IEEE Transactions on Parallel and Distributed Systems (TPDS) highlights recent advances in trust, security, and privacy for emerging parallel and distributed systems. This special issue was initiated by Dr. Xu Li, Dr. Patrick McDaniel, Dr. Radha Poovendran, and Dr. Guojun Wang. Due to a large number of submissions, Dr. Zhenfu Cao, Dr. Keqiu Li, and Dr. Yang Xiang were later invited to the editorial team. Dr. Xu Li was responsible for coordinating the paper review process. In response to the call for papers, we received 150 effective submissions, out of which 24 are included in this special issue after rigorous review and careful revision, presenting an acceptance ratio of 16 percent. The accepted papers are divided into three groups, covering issues related to trust, security, and privacy, respectively.