The power of the private workspace model

In the private workspace model of concurrency control the transaction management component of a database management system maintains a private workspace for each transaction. Data items accessed by a transaction, regardless of the access mode, are cached in the workspace. At transaction commit time, its updates are made permananet in the database. In this paper we want to focus our attention on the private workspace model as a framework for the design of concurrency control algorithms which do not require ww synchronization. We present a Two Phase Locking (2PL) derivative called Workspace 2PL (W2PL) and show that in a system employing W2PL no ww synchronization is needed and more importantly, no transaction will restart on a READ request. Furthermore, under the No Blind Writes assumption we can guarantee that no READ request will cause a transaction to starve, thus no Reader will be restarted or starved.     

工业机器人的工作空间综合

根据机器人工作位姿要求确定其自由度数，关节类型及排列，杆件尺寸，关节运动范围，机器人的位置等过程称为机器人的工作空间综合过程，本文侧重对已知的机器人结构提出了进行工作空间综合的优化方法。     

A New Cable-Based Parallel Robot with Three Degrees of Freedom

In this paper, a new cable-based parallel robot is introduced. In this robot, the cables are used to not only actuate the end-effector but apply the necessary kinematic constrains to provide three pure translational degrees of freedom. In order to maintain tension in the cables, a collapsible element called “spine” is used between the end-effector and the robot’s base. The kinematic analysis of this robot is similar to that of a rigid link parallel manipulator as long as the cables are in tension. The rigidity of this robot which corresponds to having all cables in tension is studied thoroughly and it is proved that a single spine with a finite force is sufficient to guarantee rigidity for any external load at any position of the workspace.     

Analysis of parallel kinematic machine with kinetostatic modelling method

A new method, called Kinetostatic Modelling Method is proposed for analysis of parallel kinematic machines (PKMs) in the paper. First, system modelling includes mobility study, kinematic model and inverse kinematic is conducted. Then, kinetostatic modelling is presented. It includes a complete compliant model developed for the analysis of the PKMs with fixed-length legs, with the model, two global compliance indices are introduced to provide a new mean of measuring the PKM's compliance over the workspace. These two global indices are the mean value and the standard deviation of the trace of the generalized compliance matrix. The mean value represents the average compliance of the PKM over the workspace, while the standard deviation indicates the compliance fluctuation relative to the mean value. The effect of three types of compliance is investigated in order to identify a dominant factor. The proposed method is implemented to analyze the compliance of the Tripod-based PKM prototype built at the Integrated Manufacturing Technologies Institute of the National Research Council of Canada. It is shown that the proposed method is an effective means for evaluating the kinetostatic behaviour of PKMs globally.     

Singularity-robust decoupled control of dual-elbow manipulators

The ability of a robot manipulator to move inside its workspace is inhibited by the presence of joint limits and obstacles and by the existence of singular positions in the configuration space of the manipulator. Several kinematic control strategies have been proposed to ameliorate these problems and to control the motion of the manipulator inside its workspace. The common base of these strategies is the manipulability measure which has been used to: (i) avoid singularities at the task-planning level; and (ii) to develop a singularity-robust inverse Jacobian matrix for continuous kinematic control. In this paper, a singularity-robust resolved-rate control strategy is presented for decoupled robot geometries and implemented for the dual-elbow manipulator. The proposed approach exploits the decoupled geometry of the dual-elbow manipulator to control independently the shoulder and the arm subsystems, for any desired end-effector motion, thus incurring a significantly lower computational cost compared to existing schemes.     

Autonomous robot calibration using a trigger probe

This paper presents a new robot autonomous calibration method using a trigger probe. The robot grips a simple probe (which was manufactured as a standard end-effector tool) automatically to touch constraint planes in a workspace (the locations of the constraint planes are not necessarily known exactly). The robot internal sensor measurements are recorded for kinematic calibration while the tip-point of the probe is in contact with the constraint plane. The kinematic constraint conditions are obtained from the known shape of the constraint surface, rather than from the measured reference locations in a workspace. The new method eliminates any use of external measuring devices for robot end-effector location measurements for robot calibration; thus it is suitable for a periodic robot re-calibration in a shop-floor environment. Both simulation and experimental results for a six degree-of-freedom (DOF) PUMA robot are given in this paper. The evaluation results using an external precision measuring device — Coordinate Measuring Machine(CMM) — are also presented.     

Design of a spherical parallel kinematic machine for ankle rehabilitation

Existing ankle rehabilitation robots have the limitations of insufficient motion ranges and coupled translations. An improved spherical robot has been proposed to overcome these limitations. The forward and inverse kinematic problems of this new machine are formulated and solved; the dexterity of the workspace is evaluated and the workspace has been optimized with the consideration of the motion ranges of passive joints. The operation of machine has been simulated; it will be further expanded as a control program to run the rehabilitation robot.     

A parallel robotic attachment and its remote manipulation

This paper discusses a 3-dof (degree of freedom) parallel robotic attachment and its remote manipulation. This attachment is designed as a tripod that provides two rotary motions and one linear motion. The attachment can be mounted onto a variety of machines for different applications, including CNC milling machines, industrial robots, and CMM. Java technologies are used to develop a remote manipulation system for the parallel robotic attachment, including remote monitoring and control. The main difference of this system from the existing web-based or internet-based remote systems is the way to control the motion of the machine from a remote site. Instead of using a camera for monitoring, the tripod is modeled using 3D computer graphics with behavioral control nodes embedded. Compared with camera-based solutions, network traffic is largely reduced, thereby making real-time remote device manipulation practical on the web. Our parallel robotic attachment is one type of parallel kinematic mechanisms (PKM). With PKM emerging as a new way of building flexible systems or agile machines, its advantage over serial mechanism is also presented.     

Constrained multi-objective trajectory planning of parallel kinematic machines

This paper presents a new approach to multi-objective dynamic trajectory planning of parallel kinematic machines (PKM) under task, workspace and manipulator constraints. The robot kinematic and dynamic model, (including actuators) is first developed. Then the proposed trajectory planning system is introduced. It minimizes electrical and kinetic energy, robot traveling time separating two sampling periods, and maximizes a measure of manipulability allowing singularity avoidance. Several technological constraints such as actuator, link length and workspace limitations, and some task requirements, such as passing through imposed poses are simultaneously satisfied. The discrete augmented Lagrangean technique is used to solve the resulting strong nonlinear constrained optimal control problem. A decoupled formulation is proposed in order to cope with some difficulties arising from dynamic parameters computation. A systematic implementation procedure is provided along with some numerical issues. Simulation results proving the effectiveness of the proposed approach are given and discussed.     

Kinematic modeling of Exechon parallel kinematic machine

The studies on PKMs have attracted a great attention to robotics community. By deploying a parallel kinematic structure, a parallel kinematic machine (PKM) is expected to possess the advantages of heavier working load, higher speed, and higher precision. Hundreds of new PKMs have been proposed. However, due to the considerable gaps between the desired and actual performances, the majorities of the developed PKMs were the prototypes in research laboratories and only a few of them have been practically applied for various applications; among the successful PKMs, the Exechon machine tool is recently developed. The Exechon adopts unique over-constrained structure, and it has been improved based on the success of the Tricept parallel kinematic machine. Note that the quantifiable theoretical studies have yet been conducted to validate its superior performances, and its kinematic model is not publically available. In this paper, the kinematic characteristics of this new machine tool is investigated, the concise models of forward and inverse kinematics have been developed. These models can be used to evaluate the performances of an existing Exechon machine tool and to optimize new structures of an Exechon machine to accomplish some specific tasks.     

Torque Optimizing Control with Singularity-Robustness for Kinematically Redundant Robots

A new control method for kinematically redundant manipulators having the properties of torque-optimality and singularity-robustness is developed. A dynamic control equation, an equation of joint torques that should be satisfied to get the desired dynamic behavior of the end-effector, is formulated using the feedback linearization theory. The optimal control law is determined by locally optimizing an appropriate norm of joint torques using the weighted generalized inverses of the manipulator Jacobian-inertia product. In addition, the optimal control law is augmented with fictitious joint damping forces to stabilize the uncontrolled dynamics acting in the null-space of the Jacobian-inertia product. This paper also presents a new method for the robust handling of robot kinematic singularities in the context of joint torque optimization. Control of the end-effector motions in the neighborhood of a singular configuration is based on the use of the damped least-squares inverse of the Jacobian-inertia product. A damping factor as a function of the generalized dynamic manipulability measure is introduced to reduce the end-effector acceleration error caused by the damping. The proposed control method is applied to the numerical model of SNU-ERC 3-DOF planar direct-drive manipulator.     

Artificial neural network-based kinematics Jacobian solution for serial manipulator passing through singular configurations

Singularities and uncertainties in arm configurations are the main problems in kinematics robot control resulting from applying robot model, a solution based on using Artificial Neural Network (ANN) is proposed here. The main idea of this approach is the use of an ANN to learn the robot system characteristics rather than having to specify an explicit robot system model.Despite the fact that this is very difficult in practice, training data were recorded experimentally from sensors fixed on each joint for a six Degrees of Freedom (DOF) industrial robot. The network was designed to have one hidden layer, where the input were the Cartesian positions along the X, Y and Z coordinates, the orientation according to the RPY representation and the linear velocity of the end-effector while the output were the angular position and velocities for each joint, In a free-of-obstacles workspace, off-line smooth geometric paths in the joint space of the manipulator are obtained.The resulting network was tested for a new set of data that has never been introduced to the network before these data were recorded in the singular configurations, in order to show the generality and efficiency of the proposed approach, and then testing results were verified experimentally.     

Visual motor control of a 7 DOF robot manipulator using a fuzzy SOM network

A fuzzy self-organizing map (SOM) network is proposed in this paper for visual motor control of a 7 degrees of freedom (DOF) robot manipulator. The inverse kinematic map from the image plane to joint angle space of a redundant manipulator is highly nonlinear and ill-posed in the sense that a typical end-effector position is associated with several joint angle vectors. In the proposed approach, the robot workspace in image plane is discretized into a number of fuzzy regions whose center locations and fuzzy membership values are determined using a Fuzzy C-Mean (FCM) clustering algorithm. SOM network then learns the inverse kinematics by on-line by associating a local linear map for each cluster. A novel learning algorithm has been proposed to make the robot manipulator to reach a target position. Any arbitrary level of accuracy can be achieved with a number of fine movements of the manipulator tip. These fine movements depend on the error between the target position and the current manipulator position. In particular, the fuzzy model is found to be better as compared to Kohonen self-organizing map (KSOM) based learning scheme proposed for visual motor control. Like existing KSOM learning schemes, the proposed scheme leads to a unique inverse kinematic solution even for a redundant manipulator. The proposed algorithms have been successfully implemented in real-time on a 7 DOF PowerCube robot manipulator, and results are found to concur with the theoretical findings.     

Inverse Kinematics Based Human Mimicking System using Skeletal Tracking Technology

Humanoid robots needs to have human-like motions and appearance in order to be well-accepted by humans. Mimicking is a fast and user-friendly way to teach them human-like motions. However, direct assignment of observed human motions to robot’s joints is not possible due to their physical differences. This paper presents a real-time inverse kinematics based human mimicking system to map human upper limbs motions to robot’s joints safely and smoothly. It considers both main definitions of motion similarity, between end-effector motions and between angular configurations. Microsoft Kinect sensor is used for natural perceiving of human motions. Additional constraints are proposed and solved in the projected null space of the Jacobian matrix. They consider not only the workspace and the valid motion ranges of the robot’s joints to avoid self-collisions, but also the similarity between the end-effector motions and the angular configurations to bring highly human-like motions to the robot. Performance of the proposed human mimicking system is quantitatively and qualitatively assessed and compared with the state-of-the-art methods in a human-robot interaction task using Nao humanoid robot. The results confirm applicability and ability of the proposed human mimicking system to properly mimic various human motions.     

基于末端圆周运动的可变形臂旋量参数快速标定算法

针对家庭服务机器人工作的非结构化环境,设计了一种可以根据任务需求相应地调整连杆形状的可变形操作臂．该操作臂工作空间易于拓展、灵活度较高且成本低廉．但臂形的改变也给操作臂的建模和控制带来了困难．首先,可变形臂的运动学参数发生了巨大且无规律的变化,使得固结在连杆上的坐标系脱离连杆本体,变得不可测量．其次,为适应不同任务需求,可变形臂的连杆形状需要经常改变,而传统标定方法往往追求更高的标定精度而非标定效率,因而需要开发一种耗时较短的标定方法．最后,可变形臂的标定方法必须简便而易于在家庭环境中实施．针对上述问题,本文提出了一种基于末端圆周运动的可变形臂旋量参数快速标定算法．对于任意一个旋转关节,单独转动该关节时,操作臂末端的轨迹形成了一个圆弧,且该关节轴垂直于圆弧所在平面（旋转平面）并经过圆弧的圆心．基于该性质,利用随机抽样一致性（RANSAC）算法和最小二乘算法来拟合操作臂末端轨迹,从而获取操作臂的旋量参数初值．在获取到初值的基础上,提出了一种扩展卡尔曼滤波（EKF）算法进一步优化旋量参数,提高标定精度．仿真和实验结果验证了本文方法的有效性．     

Kinematic calibration for collaborative robots on a mobile platform using motion capture system

For modern robotic applications that go beyond the typical industrial environment, absolute accuracy is one of the key properties that make this possible. There are several approaches in the literature to improve robot accuracy for a typical industrial robot mounted on a fixed frame. In contrast, there is no method to improve robot accuracy when the robot is mounted on a mobile base, which is typical for collaborative robots. Therefore, in this work, we proposed and analyzed two approaches to improve the absolute accuracy of the robot mounted on a mobile platform using an optical measurement system. The first approach is based on geometric operations used to calculate the rotation axes of each joint. This approach identifies all rotational axes, which allows the calculation of the Denavit–Hartenberg (DH) parameters and thus the complete kinematic model, including the position and orientation errors of the robot end-effector and the robot base. The second approach to parameter estimation is based on optimization using a set of joint positions and end-effector poses to find the optimal DH parameters. Since the robot is mounted on a mobile base that is not fixed, an optical measurement system was used to dynamically and simultaneously measure the position of the robot base and the end-effector. The performance of the two proposed methods was analyzed and validated on a 7-DoF Franka Emika Panda robot mounted on a mobile platform PAL Tiago-base. The results show a significant improvement in absolute accuracy for both proposed approaches. By using the proposed approach with the optical measurement system, we can easily automate the estimation of robot kinematic parameters with the aim of improving absolute accuracy, especially in applications that require high positioning accuracy.     

Error-model-based robot calibration using a modified CPC model

Selection of a proper robot kinematic model is a critical step in error-model-based robot calibration. The Denavit-Hartenberg (DH) model exhibits singularities in calibration of robots having consecutive parallel joint axes. The complete and parametrically continuous (CPC) modeling technique is one of the more versatile alternative modeling conventions designated to fit the needs of manipulator calibration. No modeling convention is, however, perfect. One “user-unfriendly” aspect of the CPC model is a condition handling technique needed, when constructing the error model, to avoid model singularities due to the adoption of the direction vectors of the joint axes as link parameters.This paper presents a modification to the CPC model which brings the model closer to the DH model. Rather than using the direction vectors of joint axes, the modified CPC (MCPC) model employs angular parameters to acommodate the required rotations for each link transformation. This modification results in a much simplified error model. The model, like the CPC model, is capable of completely describing the geometry and motion of the manipulator in a reference coordinate frame. Its error model possesses a minimum number of parameters to span the entire geometric error space and it can be made singularity-free by proper selection of the tool axis. This paper presents a calibration study of the PUMA robot using the MCPC model. A moving stereo camera system was employed for end-effector pose measurements. The MCPC error model was then used for kinematic identification. Results on the PUMA arm show that the MCPC performs well for robot calibration. The well-defined structure and user friendliness of the MCPC model may facilitate the implementation of robot calibration techniques on the factory floor.     

Model-based control of redundantly actuated parallel manipulators in redundant coordinates

Model-based control of parallel kinematics machines (PKM) relies on computationally efficient formulations in terms of a set of independent joint coordinates. Since PKM models are commonly expressed in terms of actuator or end-effector coordinates the models are not valid at input- or output-singularities, respectively. Moreover input-singularities limit the motion range of PKM. Actuation redundancy is a means to increase the singularity-free range of motion. However, due to the redundancy only a subset of the actuator coordinates constitute independent coordinates. This subset corresponds to the actuator coordinates of the non-redundant PKM, which does generally not constitute proper minimal coordinates for the entire workspace. Hence a redundantly actuated PKM (RA-PKM) controlled by a model-based controller in terms of minimal coordinates would exhibit the same limitations as the non-redundant PKM. One approach to tackle this problem is to switch between different minimal coordinates, i.e., different motion equations are used within the controller.In this contribution a computed torque and augmented PD control scheme in redundant coordinates is proposed, as an alternative to coordinate switching, and applied to the control of redundantly actuated PKM. That is, no minimal coordinates are selected. This novel formulation is numerically robust and does not suffer from input- or output-singularities. Even more the formulation is always valid except at configuration space singularities. For the redundancy resolution within the inverse dynamics the pseudoinverse of a rank deficient matrix is required, for which an explicit formulation is presented. For both controllers exponential trajectory tracking is shown. Experimental results are reported for a planar 2 DOF RA-PKM.