We present a novel fast marching gradient sampling strategy to accelerate the convergence speed of sampling-based motion planning algorithms. This strategy is based on an informed certificate set which consists of the robot states with exact collision status as well as the minimum distance and the gradient to the nearest obstacle. The informed certificate set covers almost the whole planning space such that it contains rich information for the planner. The best quality point in this set is selected as the marching seed to guide the search graph move steadily to the goal set. The distance and gradient information of the marching seed helps to generate a new sample with almost sure collision status. When a feasible solution has been found, this set can construct the restricted subset that can improve current path quality. This marching gradient sampling strategy is applied to the RRT and RRT* algorithms. Simulation experiments demonstrate that the convergence speed to a feasible solution or to the optimal solution is almost twice faster than that of the safety certificate algorithms.

As a non-parametric algorithm, empirical copula is an effective way to estimate the dependence structure of high-dimension arbitrarily distributed data. However, it suffers from the problem of huge computation time because of its high computational complexity. In this paper, fuzzy empirical copula is proposed to solve this problem by combining the fuzzy clustering by local approximation of memberships (FLAME) with empirical copula. In the proposed algorithm, FLAME is extended from two-dimension data to high-dimension data and FLAME+is implemented to identify the highest density objects which represent the original dataset, and then empirical copula is used to estimate its independence structure according to the new dataset. Case studies have been carried out to demonstrate the effectiveness of the fuzzy empirical copula.

A two-stage algorithm, called switching-based adaptive weighted mean filter, is proposed to remove salt-and-pepper noise from the corrupted images. First, the directional difference based noise detector is used to identify the noisy pixels by comparing the minimum absolute value of four mean differences between the current pixel and its neighbors in four directional windows with a predefined threshold. Then, the adaptive weighted mean filter is adopted to remove the detected impulses by replacing each noisy pixel with the weighted mean of its noise-free neighbors in the filtering window. Numerous simulations demonstrate that the proposed filter outperforms many other existing algorithms in terms of effectiveness in noise detection, image restoration and computational efficiency.

Deformations of contacts between the workpiece and locators/clamps resulting from large contact forces cause overall workpiece displacement, and affect the localization accuracy of the workpiece. An important characteristic of a workpiece-fixture system is that locators are passive elements and can only react to clamping forces and external loads, whereas clamps are active elements and apply a predetermined normal load to the surface of workpiece to prevent it from losing contact with the locators. Clamping forces play an important role in determining the final workpiece quality. This paper presents a general method for determining the optimal clamping forces including their magnitudes and positions. First, we derive a set of “compatibility” equations that describe the relationship between the displacement of the workpiece and the deformations at contacts. Further, we develop a locally elastic contact model to characterize the nonlinear coupling between the contact force and elastic deformation at the individual contact. We define the minimum norm of the elastic deformations at contacts as the objective function, then formulate the problem of determining the optimal clamping forces as a constrained nonlinear programming problem which guarantees that the fixturing of the workpiece is force closure. Using the exterior penalty function method, we transform the constrained nonlinear programming into an unconstrained nonlinear programming which is, in fact, the nonlinear least square. Consequently, the optimal magnitudes and positions of clamping forces are obtained by using the Levenberg–Marquardt method which is globally convergent. The proposed planning method of optimal clamping forces, which may also have an application to other passive, indeterminate problems such as power grasps in robotics, is illustrated with numerical example.

A novel filter based on mathematical morphology for high probability impulse noise removal is presented. First, an impulse noise detector using mathematical residues is proposed to identify pixels that are contaminated by the salt or pepper noise. Then the image is restored using specialized open-close sequence algorithms that apply only to the noisy pixels. Finally, black and white blocks that degrade the quality of the image will be recovered by a block smart erase method. Experimental results demonstrate that the proposed filter outperforms a number of existing algorithms and is particularly effective for the very highly corrupted images

To realize the fast and accurate detection of the edges from the blurry images, the fast multilevel fuzzy edge detection (FMFED) algorithm is proposed. The FMFED algorithm first enhances the image contrast by means of the fast multilevel fuzzy enhancement (FMFE) algorithm using the simple transformation function based on two image thresholds. Second, the edges are extracted from the enhanced image by the two-stage edge detection operator that identifies the edge candidates based on the local characteristics of the image and then determines the true edge pixels using the edge detection operator based on the extremum of the gradient values. Experimental results demonstrate that the FMFED algorithm can extract the thin edges and remove the false edges from the image, which leads to its better performance than the Sobel operator, Canny operator, traditional fuzzy edge detection algorithm, and other multilevel fuzzy edge detection algorithms

The rigid complex fixture is presented as a mathematical model for the analysis and design of a fixture that contains more fingers than needed for immobilizing an object alone. But the fixture with more fingers may act in violation of the approachability and accessibility conditions. So we propose the design principle for a complex fixture: the finger set must be accessible; the distance from a workpiece to the finger set should be selected such that the workpiece can be in contact with all locators simultaneously; the clamping force should enable the workpiece to be in contact with all of the locators (approachable). Furthermore, we develop a new efficient procedure of analysis and verification in screw space based on the linear programming formulation and the geometric interpretation of the rigid fixture model. In addition, we introduce a new quantitative test for force closure, captured by a function that measures how far a fixture is from achieving force closure. Locating the table problem, as a complex fixture prototype, is investigated in detail to gain a great insight into the mathematical model and the analysis procedure for the rigid complex fixture. Note to Practitioners-This paper is concerned with the parameter design and verification of a complex fixture that consists of more locators, supports, and clamps than needed for force closure. There are two essential issues related to the design problems: 1) the test on whether the workpiece can be in contact with all locators simultaneously (approachable) and 2) the test on whether the workpiece can reach the desired location smoothly (accessible). A procedure for system analysis and performance verification of the rigid complex fixture is outlined in this paper. In the procedure, a linear programming with its dual formulation is applied to establish the sufficient condition for the stable state and to recognize the locators and supports. A performance index is provided to verify if a fixture is accessible, and a quantitative test is used to check whether a fixture has force closure. In the future, the linear and nonlinear compliance models of complex fixtures will be discussed and incorporated with this rigid model for the implementation of a complete analysis and design tool of the complex fixture

Rule-based production scheduling is analyzed from the perspective of closed-loop control. An integrated feedback control methodology is proposed to enhance the performance of rule-based scheduling. The integrated control system consists of a state feedback control module, a performance-based feedback module, and a supervisory control module. Performance criteria are analyzed and classified into job-related and resource-related criteria. The key factors of performance are identified and used as state variables in the feedback control. The performance-based feedback control compensates for the errors that are caused by the scheduling rules. The supervisory control is designed to enhance the overall performance by adjusting the feedforward gains according to scheduling objectives. Simulation results show that the integrated control scheme can significantly improve the overall performance of the scheduling system.

The advanced sensor networks play an increasingly important role to promote maintenance strategy shifting from traditional periodic maintenance to proactive e-maintenance in modern industry. IP sensor, a smart device that is Internet visible and capable, have been implemented in the paper, which has compliant STIM data structure described by IEEE 1451.2 standard, while an IP module is presented and adopted herein to instead NCAP to enable sensors entering into Internet in an easy and cost-effective way. It provides a powerful tool to gather information at plant level of the distributed application to enable remote maintenance engineering transparently monitoring and operating the field devices over Internet in e-maintenance system. Finally, a full working prototype of the system is realized, and two experiments have been conducted to experimentally verify the IP sensor proposed herein are feasible and suitable for distributed applications under LAN environment.

Presented is the complex fixture, as a mathematical model, for the purpose of designing large-scale fixture, planning force assembly, synthesizing mechanism tolerance and analyzing contact restraint. In contrast to a simplex fixture, a complex fixture is not necessarily accessible and deterministic. In order to recognize what is an effective fixel, and what is an active fixel for a complex fixture, a set of fundamental equations is developed, such as locating equation (1), rigidity constraint (2), clamping equation (3), and compliance model (4) etc. A complex fixture is regarded as a rigid fixture system (RFS), if it can be algebraically described by (1), (2), and (3). A complex fixture is an elastic fixture system (EFS), if it can be algebraically described by (1), (3), and (4). By exploiting equations (3) and (2), we may construct different geometrical primitives both in wrench space and in twist space to characterize a complex fixture. Based on the duality of (3) and (2), any RSF can be represented by a pair of linear programs: the primal P and the dual D.

The general algorithm for manufacturability analysis of 5-axis sculptured surface machining is presented. The visibility cone which represents the aggregate of all visible directions is constructed to describe geometric constraints. Combined with the convex hull computation algorithm, a detailed procedure for computing the visibility cone has been developed. Through the geometric constraint analysis, the manufacturability for sculptured surface machining is evaluated so that geometric defects and inefficiencies can be inspected and corrected at the earlier design stages. Hence reworks in product development can be reduced or even avoided and the concurrence of sculptured surface design and manufacturing can be enhanced.