Hanqi Zhuang

Self-calibration of parallel mechanisms with a case study on Stewart platforms

Self-calibration has the potential of: 1) removing the dependence on any external pose sensing information; 2) producing high accuracy measurement data over the entire workspace of the system with an extremely fast measurement rate; 3) being automated and completely noninvasive; 4) facilitating on-line accuracy compensation; and 5) being cost effective. A general framework is introduced in this paper for the self-calibration of parallel manipulators. The concept of creating forward and inverse measurement residuals by exploring conflicting information provided with redundant sensing is proposed. Some of these ideas have been widely used for robot calibration when robot end-effector poses are available. By this treatment, many existing kinematic parameter estimation techniques can be applied for the self-calibration of parallel mechanisms. It is illustrated through a case study, i.e. calibration of the Stewart platform, that with this framework the design of a suitable self-calibration system and the formulation of the relevant mathematical model become more systematic. A few principles important to the system self-calibration are also demonstrated through the case study. It is shown that by installing a number of redundant sensors on the Stewart platform, the system is able to perform self-calibration. The approach provides a tool for rapid and autonomous calibration of the parallel mechanism.

On improving eye feature extraction using deformable templates

Abstract An improved method of extracting eye features from facial images using eye templates is described. It retains all advantages of the deformable template method originally proposed by A. L. Yuille, P. W. Hallinan and D. S. Cohen ( Int. J. Comput. Vision 99–111 (1989)) and rectifies some of its weaknesses. This is achieved by the following modifications. First, the original eye template and the overall energy function to represent the most salient features of the eye are modified. Secondly, in order to simplify the issue of selecting weights for the energy terms, the value of each energy term is normalized in the range 0–1 and only two different weights are assigned. This weighting schedule does not require expert knowledge therefore it is more user friendly. Thirdly, all parameters of the template are changed simultaneously during the minimization process rather than using a sequential procedure. This scheme prevents some parameters of the eye template from being overly changed, helps the algorithm to converge to the global minimum, and reduces the processing time. The selection of initial parameters of the eye template is based on an eye window obtained in preprocessing. Experimental results are presented to demonstrate the efficacy of the algorithm. A comparison study of various processing schemes is also given.

Simultaneous robot/world and tool/flange calibration by solving homogeneous transformation equations of the form AX=YB

The paper presents a linear solution that allows a simultaneous computation of the transformations from robot world to robot base and from robot tool to robot flange coordinate frames. The flange frame is defined on the mounting surface of the end-effector. It is assumed that the robot geometry, i.e., the transformation from the robot base frame to the robot flange frame, is known with sufficient accuracy, and that robot end-effector poses are measured. The solution has applications to accurately locating a robot with respect to a reference frame, and a robot sensor with respect to a robot end-effector. The identification problem is cast as solving a system of homogeneous transformation equations of the form A/sub i/X=YB/sub i/,i=1, 2, ..., m. Quaternion algebra is applied to derive explicit linear solutions for X and Y provided that three robot pose measurements are available. Necessary and sufficient conditions for the uniqueness of the solution are stated. Computationally, the resulting solution algorithm is noniterative, fast and robust. >

Simultaneous calibration of a robot and a hand-mounted camera

A popular configuration widely used in a variety of robotic applications is to mount a camera on the robot manipulator hand. Before performing a measurement task using such a system, both the camera and the robot need to be calibrated. In this paper, a procedure is developed for simultaneous calibration of a robot and a monocular camera. Unlike conventional approaches based on first calibrating the camera and then calibrating the robot, the algorithm solves for the kinematic parameters of the robot and camera in one stage, thus eliminating error propagation and improving noise sensitivity. Only two parameters are added to a robot calibration model to represent camera geometry. With this addition, different levels of calibration can be done under a unified framework. An error model relating-image measurement residuals to kinematic parameter deviations is derived. Simulation and experimental studies have been conducted to assess the effectiveness of the proposed procedure. >

On the accuracy of a Stewart platform. II. Kinematic calibration and compensation

An effective algorithm for the identification of the kinematic parameters of a Stewart platform is presented and verified through simulations. The algorithm can be applied to both the reduced and the full models, which differ by the number of parameters to be identified. Compensation procedures for models are also presented. The algorithm was tested using simulated measurements that included realistic measurement noise, and the results showed that the platform pose error was reduced by at least one order of magnitude. The identification algorithm is computationally expensive and has to be performed on a powerful computer for practical implementation.<<ETX>>

A complete and parametrically continuous kinematic model for robot manipulators

A kinematic modeling convention for robot manipulators is proposed. The kinematic model has complete and parametrically continuous (CPC) properties. The parametric continuity of the CPC model is achieved by adopting a singularity-free line representation. Completeness is achieved through adding two link parameters which allow arbitrary placement of link coordinate frames. The transformation from the base frame to the world frame and from the tool frame to the last link frame can be modeled with the same convention as that used for internal link transformations. These parameters make the CPC model particularly useful for robot calibration.<<ETX>>

Self-calibration of a class of parallel manipulators

A general numerical method is introduced in this paper for the self-calibration of parallel manipulators. The concept of creating inverse measurement residuals by exploring conflicting information provided with redundant sensing is generalized. A numerical kinematic analysis method is adopted to systematically compute the inverse measurement residuals. By this treatment, the design of a suitable self-calibration system became more systematic, and existing kinematic parameter estimation techniques can be applied for the self-calibration of parallel mechanisms. It is shown that by installing 2 or more redundant sensors on the Stewart platform, the system is able to perform self-calibration. It is possible to calibrate part of the system using a reduced number of redundant sensors; the identification algorithm converges rapidly; its accuracy performance is satisfactory; and the extension of the method to other parallel manipulators is straightforward.

Optimal selection of measurement configurations for robot calibration using simulated annealing

Measuring robot positions and orientations is a crucial step in a robot calibration process. Off-line optimal selection of measurement configurations can significantly improve the accuracy of kinematic identification. Since the dimension of the parameter space is very large and the cost function is highly nonlinear, this selection process could be well beyond the capacity of todays computers if a global optimal solution is sought by an exhaustive search. On the other hand, gradient-based algorithms are often trapped into local minima. A simulated annealing (SA) approach is adopted in this paper to obtain optimal or near optimal measurement configurations for robot calibration. Simulated annealing is capable of overcoming local minimum points. It is also very convenient for the inclusion of joint travel limits. The SA algorithm is costly computationally; however, since optimal configuration selection can be performed off-line, this may not be a serious problem. To accelerate the convergence rate, a suitable cooling schedule is devised. Practical implementation considerations are discussed. Experimental results are presented to demonstrate the feasibility of the proposed approach.<<ETX>>

Corner detection by a cost minimization approach

Abstract Corner detection, which is a valuable tool in biological and machine vision systems, is cast as a problem of cost optimization. The cost function is suitably devised to capture different desirable characteristics of corners such as edginess, curvature and region dissimilarity. The geometrical structure of the corner as well as the gray level variation of the image are accounted for in cost factors to evaluate the quality of corner configurations. The cost function is minimized using a simulated annealing algorithm. This approach also provides corner orientations and angles in addition to corner locations. The efficacy of the approach is demonstrated by experimental results.

Advanced Fuzzy Logic Technologies in Industrial Applications

This book introduces a dynamic, on-line fuzzy inference system. In this system membership functions and control rules are not determined until the system is applied and each output of its lookup table is calculated based on current inputs. The book describes the real-world uses of new fuzzy techniques to simplify readers tuning processes and enhance the performance of their control systems. It further contains application examples.