Optimal design of a 2-DOF pick-and-place parallel robot using dynamic performance indices and angular constraints

This paper presents an approach for the optimal design of a 2-DOF translational pick-and-place parallel robot. By taking account of the normalized inertial and centrifugal/Coriolis torques of a single actuated joint, two global dynamic performance indices are proposed for minimization. The pressure angles within a limb and between two limbs are considered as the kinematic constraints to prevent direct and indirect singularities. These considerations together form a multi-objective optimization problem that can then be solved by the modified goal attainment method. A numerical example is discussed. A number of robots designed by this approach have been integrated into production lines for carton packing in the pharmaceutical industry

Optimal design of a 2-DOF pick-and-place parallel robot using dynamic performance indices and angular constraints

This paper presents an approach for the optimal design of a 2-DOF translational pick-and-place parallel robot. By taking account of the normalized inertial and centrifugal/Coriolis torques of a single actuated joint, two global dynamic performance indices are proposed for minimization. The pressure angles within a limb and between two limbs are considered as the kinematic constraints to prevent direct and indirect singularities. These considerations together form a multi-objective optimization problem that can then be solved by the modified goal attainment method. A numerical example is discussed. A number of robots designed by this approach have been integrated into production lines for carton packing in the pharmaceutical industry

Optimal kinematic design of 2-DOF parallel manipulators with well-shaped workspace bounded by a specified conditioning index

This paper presents a hybrid method for the optimum kinematic design of two-degree-of-freedom (2-DOF) parallel manipulators with mirror symmetrical geometry. By taking advantage of both local and global approaches, the proposed method can be implemented in two steps. In the first step, the optimal architecture, in terms of isotropy and the behavior of the direct Jacobian matrix, is achieved, resulting in a set of closed-form parametric relationships that enable the number of design variables to be reduced. In the second step, the workspace bounded by the specified conditioning index is generated, which allows only one design parameter to be determined by optimizing a comprehensive index in a rectangular workspace. The kinematic optimization of a revolute-jointed 2-DOF parallel robot has been taken as an example to illustrate the effectiveness of this approach

Simulation and Optimisation of a Two Degree of Freedom, Planar, Parallel Manipulator

Development in pick-and-place robotic manipulators continues to grow as factory processes are streamlined. One configuration of these manipulators is the two degree of freedom, planar, parallel manipulator (2DOFPPM). A machine building company, RML Engineering Ltd., wishes to develop custom robotic manipulators that are optimised for individual pick-and-place applications. This thesis develops several tools to assist in the design process. The 2DOFPPM’s structure lends itself to fast and accurate translations in a single plane. However, the performance of the 2DOFPPM is highly dependent on its dimensions. The kinematics of the 2DOFPPM are explored and used to examine the reachable workspace of the manipulator. This method of analysis also gives insight into the relative speed and accuracy of the manipulator’s end-effector in the workspace. A simulation model of the 2DOFPPM has been developed in Matlab’s® SimMechanics®. This allows the detailed analysis of the manipulator’s dynamics. In order to provide meaningful input into the simulation model, a cubic spline trajectory planner is created. The algorithm uses an iterative approach of minimising the time between knots along the path, while ensuring the kinematic and dynamic limits of the motors and end-effector are abided by. The resulting trajectory can be considered near-minimum in terms of its cycle-time. The dimensions of the 2DOFPPM have a large effect on the performance of the manipulator. Four major dimensions are analysed to see the effect each has on the cycle-time over a standardised path. The dimensions are the proximal and distal arms, spacing of the motors and the height of the manipulator above the workspace. The solution space of all feasible combinations of these dimensions is produced revealing cycle-times with a large degree of variation over the same path. Several optimisation algorithms are applied to finding the manipulator configuration with the fastest cycle-time. A random restart hill-climber, stochastic hill-climber, simulated annealing and a genetic algorithm are developed. After each algorithm’s parameters are tuned, the genetic algorithm is shown to outperform the other techniques

Simulation and Optimisation of a Two Degree of Freedom, Planar, Parallel Manipulator

Development in pick-and-place robotic manipulators continues to grow as factory processes are streamlined. One configuration of these manipulators is the two degree of freedom, planar, parallel manipulator (2DOFPPM). A machine building company, RML Engineering Ltd., wishes to develop custom robotic manipulators that are optimised for individual pick-and-place applications. This thesis develops several tools to assist in the design process. The 2DOFPPM’s structure lends itself to fast and accurate translations in a single plane. However, the performance of the 2DOFPPM is highly dependent on its dimensions. The kinematics of the 2DOFPPM are explored and used to examine the reachable workspace of the manipulator. This method of analysis also gives insight into the relative speed and accuracy of the manipulator’s end-effector in the workspace. A simulation model of the 2DOFPPM has been developed in Matlab’s® SimMechanics®. This allows the detailed analysis of the manipulator’s dynamics. In order to provide meaningful input into the simulation model, a cubic spline trajectory planner is created. The algorithm uses an iterative approach of minimising the time between knots along the path, while ensuring the kinematic and dynamic limits of the motors and end-effector are abided by. The resulting trajectory can be considered near-minimum in terms of its cycle-time. The dimensions of the 2DOFPPM have a large effect on the performance of the manipulator. Four major dimensions are analysed to see the effect each has on the cycle-time over a standardised path. The dimensions are the proximal and distal arms, spacing of the motors and the height of the manipulator above the workspace. The solution space of all feasible combinations of these dimensions is produced revealing cycle-times with a large degree of variation over the same path. Several optimisation algorithms are applied to finding the manipulator configuration with the fastest cycle-time. A random restart hill-climber, stochastic hill-climber, simulated annealing and a genetic algorithm are developed. After each algorithm’s parameters are tuned, the genetic algorithm is shown to outperform the other techniques

A Flexible, Low-Power, Programmable Unsupervised Neural Network Based on Microcontrollers for Medical Applications

We present an implementation and laboratory tests of a winner takes all (WTA) artificial neural network (NN) on two microcontrollers (μC) with the ARM Cortex M3 and the AVR cores. The prospective application of this device is in wireless body sensor network (WBSN) in an on-line analysis of electrocardiograph (ECG) and electromyograph (EMG) biomedical signals. The proposed device will be used as a base station in the WBSN, acquiring and analysing the signals from the sensors placed on the human body. The proposed system is equiped with an analog-todigital converter (ADC), and allows for multi-channel acquisition of analog signals, preprocessing (filtering) and further analysis