Singularity and controllability analysis of parallel manipulators and closed-loop mechanisms

This paper presents a study of kinematic and force singularities in parallel manipulators and closed-loop mechanisms and their relationship to accessibility and controllability of such manipulators and closed-loop mechanisms, Parallel manipulators and closed-loop mechanisms are classified according to their degrees of freedom, number of output Cartesian variables used to describe their motion and the number of actuated joint inputs. The singularities in the workspace are obtained by considering the force transformation matrix which maps the forces and torques in joint space to output forces and torques ill Cartesian space. The regions in the workspace which violate the small time local controllability (STLC) and small time local accessibility (STLA) condition are obtained by deriving the equations of motion in terms of Cartesian variables and by using techniques from Lie algebra.We show that for fully actuated manipulators when the number ofactuated joint inputs is equal to the number of output Cartesian variables, and the force transformation matrix loses rank, the parallel manipulator does not meet the STLC requirement. For the case where the number of joint inputs is less than the number of output Cartesian variables, if the constraint forces and torques (represented by the Lagrange multipliers) become infinite, the force transformation matrix loses rank. Finally, we show that the singular and non-STLC regions in the workspace of a parallel manipulator and closed-loop mechanism can be reduced by adding redundant joint actuators and links. The results are illustrated with the help of numerical examples where we plot the singular and non-STLC/non-STLA regions of parallel manipulators and closed-loop mechanisms belonging to the above mentioned classes. (C) 2000 Elsevier Science Ltd. All rights reserved.

Scheduling identical parallel machines with machine eligibility restrictions to minimize total weighted flowtime in automobile gear manufacturing

In this paper, we address a scheduling problem for minimizing total weighted flowtime, observed in automobile gear manufacturing. Specifically, the bottleneck operation of the pre-heat treatment stage of gear manufacturing process has been dealt with in scheduling. Many real-life scenarios like unequal release times, sequence dependent setup times, and machine eligibility restrictions have been considered. A mathematical model taking into account dynamic starting conditions has been proposed. The problem is derived to be NP-hard. To approach the problem, a few heuristic algorithms have been proposed. Based on planned computational experiments, the performance of the proposed heuristic algorithms is evaluated: (a) in comparison with optimal solution for small-size problem instances and (b) in comparison with the estimated optimal solution for large-size problem instances. Extensive computational analyses reveal that the proposed heuristic algorithms are capable of consistently yielding near-statistically estimated optimal solutions in a reasonable computational time.

Parallel Networks for Machine Vision

The amount of computation required to solve many early vision problems is prodigious, and so it has long been thought that systems that operate in a reasonable amount of time will only become feasible when parallel systems become available. Such systems now exist in digital form, but most are large and expensive. These machines constitute an invaluable test-bed for the development of new algorithms, but they can probably not be scaled down rapidly in both physical size and cost, despite continued advances in semiconductor technology and machine architecture. Simple analog networks can perform interesting computations, as has been known for a long time. We have reached the point where it is feasible to experiment with implementation of these ideas in VLSI form, particularly if we focus on networks composed of locally interconnected passive elements, linear amplifiers, and simple nonlinear components. While there have been excursions into the development of ideas in this area since the very beginnings of work on machine vision, much work remains to be done. Progress will depend on careful attention to matching of the capabilities of simple networks to the needs of early vision. Note that this is not at all intended to be anything like a review of the field, but merely a collection of some ideas that seem to be interesting.

Single machine scheduling and due date assignment under series-parallel precedence constraints

We consider a single machine due date assignment and scheduling problem of minimizing holding costs with no tardy jobs tinder series parallel and somewhat wider class of precedence constraints as well as the properties of series-parallel graphs.

Kinematic Design of a 6-DOF Parallel Manipulator with Decoupled Translation and Rotation

A new three-limb, six-degree-of-freedom (DOF) parallel manipulator (PM), termed a selectively actuated PM (SA-PM), is proposed. The end-effector of the manipulator can produce 3-DOF spherical motion, 3-DOF translation, 3-DOF hybrid motion, or complete 6-DOF spatial motion, depending on the types of the actuation (rotary or linear) chosen for the actuators. The manipulator architecture completely decouples translation and rotation of the end-effector for individual control. The structure synthesis of SA-PM is achieved using the line geometry. Singularity analysis shows that the SA-PM is an isotropic translation PM when all the actuators are in linear mode. Because of the decoupled motion structure, a decomposition method is applied for both the displacement analysis and dimension optimization. With the index of maximal workspace satisfying given global conditioning requirements, the geometrical parameters are optimized. As a result, the translational workspace is a cube, and the orientation workspace is nearly unlimited.

Effects of Constraint Errors on Parallel Manipulators with Decoupled Motion

From perspective of structure synthesis, certain special geometric constraints, such as joint axes intersecting at one point or perpendicular to each other, are necessary in realizing the end-effector motion of kinematically decoupled parallel manipulators (PMs) along individual motion axes. These requirements are difficult to achieve in the actual system due to assembly errors and manufacturing tolerances. Those errors that violate the geometric constraint requirements are termed “constraint errors”. The constraint errors usually are more troublesome than other manipulator errors because the decoupled motion characteristics of the manipulator may no longer exist and the decoupled kinematic models will be rendered useless due to these constraint errors. Therefore, identification and prevention of these constraint errors in initial design and manufacturing stage are of great significance. In this article, three basic types of constraint errors are identified, and an approach to evaluate the effects of constraint errors on decoupling characteristics of PMs is proposed. This approach is illustrated by a 6-DOF PM with decoupled translation and rotation. The results show that the proposed evaluation method is effective to guide design and assembly.

Type Synthesis of 3-DOF Multi-Mode Translational/Spherical Parallel Mechanisms with Lockable Joints

A 3-DOF (degrees-of-freedom) multi-mode translational/spherical PM (parallel mechanism) with lockable joints is a novel reconfigurable PM. It has both 3-DOF spatial translational operation mode and 3-DOF spherical operation mode. This paper presents an approach to the type synthesis of translational/spherical PMs with lockable joints. Using the proposed approach, several 3-DOF translational/spherical PMs are obtained. It is found that these translational/spherical PMs do not encounter constraint singular configurations and self-motion of sub-chain of a leg during reconfiguration. The approach can also be used for synthesizing other classes of multi-mode PMs with lockable joints, multi-mode PMs with variable kinematic joints, partially decoupled PMs, and reconfigurable PMs with a reconfigurable platform.

Android Malware Detection Using Parallel Machine Learning Classifiers

Mobile malware has continued to grow at an alarming rate despite on-going mitigation efforts. This has been much more prevalent on Android due to being an open platform that is rapidly overtaking other competing platforms in the mobile smart devices market. Recently, a new generation of Android malware families has emerged with advanced evasion capabilities which make them much more difficult to detect using conventional methods. This paper proposes and investigates a parallel machine learning based classification approach for early detection of Android malware. Using real malware samples and benign applications, a composite classification model is developed from parallel combination of heterogeneous classifiers. The empirical evaluation of the model under different combination schemes demonstrates its efficacy and potential to improve detection accuracy. More importantly, by utilizing several classifiers with diverse characteristics, their strengths can be harnessed not only for enhanced Android malware detection but also quicker white box analysis by means of the more interpretable constituent classifiers.

Kinematic and dynamic modeling of a robotic head with linear motors

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.

High-precision five-axis machine for high-speed material processing using linear motors and parallel-serial kinematics

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.

Two-mode overconstrained three-DOFs rotational-translational linear-motor-based parallel-kinematics mechanism for machine tool applications

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.