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Multirobot systems have shown great potential in dealing with complicated tasks that are impossible for a single robot to achieve. One essential problem encountered in cooperatively working of the multirobot systems is the unknown initial transformation relationships from hand to eye, base to base, and flange to tool. In this article, the problem of multicoordinates calibration for a dual-robot system is formulated to a matrix equation AXB = YCZ. A novel approach for simultaneously solving the unknowns in equation AXB = YCZ is proposed, which is composed of a closed form method based on the Kronecker product and an iterative method which converts the calculation of a nonlinear problem to an optimization problem of a strictly convex function. The closed form method is used to quickly obtain an initial estimation for the iterative method to improve the efficiency and accuracy of iteration. In addition, a series of conditions on the solvability of the problem are proposed to guide the operators to select appropriate robot attitudes during the calibration process. To show the feasibility and superiority of the proposed iterative method, two other calibration methods are chosen to be compared to the proposed method through simulation and practical experiments. The comparison results verify the superiority of the proposed method in accuracy, efficiency, and stability. [ABSTRACT FROM AUTHOR]

Scanner-based robotic grinding has shown great potential for replacing the manual method to achieve efficient and automatic manufacturing. However, its application has been limited by the grinding quality, which is affected by the pose errors between the robot and other workcells (a scanner, a workpiece, and a tool). To improve the pose accuracy, this article proposes a novel estimation method for above three pose errors, where a cylinder is used as the calibration object. Using differential kinematics, the relationship between the hand-eye pose error and the reconstructed error is built. The hand-eye pose error is estimated by scanning and reconstructing a cylinder. An iterative method is presented to find the optimized orientation error vector, avoiding the uncertain error of multiple solutions using the Schmidt method. Based on the speed adjoint transformation, a mathematical model between the workpiece/tool pose errors and grinding error is built. Then, an experimental estimation approach for the workpiece/tool pose errors is presented by shape matching the measured points of the grinded cylinder with the design model. Unlike the traditional static construction method, this method uses large-scale measured points with high measurement accuracy to improve the estimation accuracy and stability and can estimate the pose error caused during the dynamic grinding process, such as vibration and force deformation. Finally, pose error estimation and compensation experiments are performed to verify the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Free-form surface matching that aligns measured points with a design model is a common problem in manufacturing automation. In this paper, an iterative variance-minimization matching (VMM) method is proposed to address measured points that have measuring defects, such as uneven/open point distributions and measuring noise. The basic idea is that the objective function is defined as the variance of the closest distance from each measured point to the design model, and the measuring defects are considered by incorporating an average distance item into the objective function. Using the defined average distance item, a strategy for analyzing the effect of measuring defects on VMM and existing methods is presented. It is shown that the VMM method does not easily become trapped in a local optimum when measuring defects exist. To consider convergence speed and convergence stability, a new distance based on the first-order point-to-point distance and point-to-tangent distance is developed and used in the objective function. To demonstrate the availability of the proposed method, quadratic convergence and positive definiteness are theoretically analyzed. The proposed method is efficient and insensitive to measuring defects and is useful for shape matching tasks involving free-form surface features. Note to Practitioners—This paper is motivated by the problem of matching measured points with a design model to automate manufacturing processes such as geometric inspection, workpiece localization, and allowance distribution. Measured points are obtained by applying a scanning device where measuring defects usually appear. Existing matching methods suffer from the drawback that the measured points may incline toward dense data and become trapped in a local optimum, due to measuring defects. To address this practical issue, this paper proposes a new method called variance-minimization matching (VMM), in which the objective function is optimized to weaken the effect of measuring defects. By examining the differences between VMM and existing methods, it is found that VMM can achieve quadratic convergence speed. Most importantly, the method is insensitive to uneven/open point distributions. In summary: 1) this method allows us to improve the matching accuracy in the presence of measuring defects; 2) there is no need to obtain a high-quality scan of the entire workpiece, potentially reducing scanning difficulty and improving scanning efficiency; and 3) the requirement of uniform sampling for measured points is reduced. [ABSTRACT FROM AUTHOR]

In the first part of this paper, a free-form surface matching method called variance-minimization matching (VMM) was proposed to address uneven/open point distributions and measuring noise. The convergence property and sensitivity to measuring defects were theoretically studied. In the second part of this paper, a series of experiments are presented to verify the feasibility of the proposed method in free-form surface matching. The experiments are divided into four sets: a measuring defects experiment, a noise experiment, a convergence experiment, and an artificial experiment. In the first set of experiments, the existing methods are prone to becoming trapped in a local optimum affected by uneven/open point distributions, which shows that measured points incline toward dense areas. However, in VMM, there is little inclination regardless of the increase in the number of measuring defects. In the second set of experiments, sensitivity to varying noise is tested. The results show that VMM helps prevent unstable sliding in the presence of Gaussian noise. In the third set of experiments, we compare convergence speed and convergence stability under different initial positions. It is verified that VMM exhibits the quadratic convergence. Finally, a set of artificial experiments is implemented, revealing that the proposed method is appropriate for use in automated manufacturing processes such as geometric inspection and allowance distribution. Note to Practitioners—Measuring defects usually occur when using a scanning device to obtain the measured points of a workpiece. Weakening the effect of measuring defects on matching results is critical to promoting manufacturing automation. This paper proposes a new method called variance-minimization matching (VMM) that considers measuring defects. In the first part of this paper, the modeling and theoretical analysis of VMM were introduced. In the second part of this paper, simulated experiments are performed to verify the feasibility of VMM in addressing uneven/open point distributions, measuring noise, and large initial positions. Next, artificial experiments employing VMM in geometric inspection and allowance distribution are presented. The proposed method also applies to other automated manufacturing processes, such as workpiece localization, deformation analysis, and complex parts repair. [ABSTRACT FROM AUTHOR]

Inspecting an impeller is a challenging task in manufacturing automation due to its free-form surface and overlapping and twisted blades. Existing inspection method by a Coordinate Measuring Machine is complex and time consuming, because of offline reclamping and manual operation. Automatic on-machine inspection without transferring and reclamping workpiece is a promising technique, and has found an extensive application in recent years. This paper proposes a novel method of interference-free inspection path generation for impeller blades using an on-machine probe. The accessibility cone is defined to search for the approach direction vectors of a probe cylinder, whereby the sizes of both cylinder rod and cylinder disk are considered. Then, the idea of area sweeping minimization is applied to construct an objective function from which required direction vectors of the probe cylinder in a smooth path are easily solved. The generated path can avoid the interference and collision between a moving probe cylinder with the overlapping blades, and guarantee stable speed and acceleration of the rotary motions of the five-axis machine tool. Its effectiveness is verified by the on-machine inspection experiments. [ABSTRACT FROM PUBLISHER]

Optical inspection of blades is important in computer vision and manufacturing automation. One problem commonly encountered is that the scanned point cloud may be polluted by noise, mainly from the scanning equipment. How to smooth the blade surface while preserving the thin-walled feature of leading/trailing edges is a challenging task. In this paper, we propose an adaptive bilateral method for the smoothing of a point-sampled surface. This paper is motivated by a bilateral filtering technique of a two-dimensional image. The basis of the method is the application of information entropy to distinguish density difference of point cloud. By minimizing defined smoothing density entropy and preserving density entropy, the optimal surface-smoothing factor and feature-preserving factor are calculated at each vertex. Applying the obtained factors, the objective of smoothing surface while preserving thin-walled feature is achieved, which overcomes the feature shrinking/shriveling problem. Our method does not require surface triangulation or curvature computation, and is very suitable for the object of a point-sampled surface with high-curvature feature or sharp features. Its robustness and efficiency are confirmed by experiments. [ABSTRACT FROM PUBLISHER]

Robotic grinding is a promising technique to generate the final shape of blades. It can relieve human from participating in dirty and noisy environments, improve product quality, and lower production costs. One important task in robotic grinding is 3-D shape matching. However, existing matching methods do not consider the requirements associated with different grinding allowances, which can potentially lead to an unstable grinding force. This paper proposes a novel shape matching method for robotic grinding. The goal is to define a new objective function considering different allowance weights for stable grinding, and address incorrect shape matching from the missing points or uneven density points. The main contribution of this paper is the application of variance minimization to construct an objective function, from which the required shape matching parameters are iteratively calculated. This method balances the contributions of all the measured points, weighs the allowances for the pressure and suction surfaces of a blade, and avoids incorrect matching tendencies for high-density points. It is advantageous to maintaining a relatively stable grinding force. The effectiveness of this method is verified through simulations and scanning/grinding experiments of different blades. [ABSTRACT FROM PUBLISHER]

Linear induction motors (LIMs) are being gradually applied in the urban rail transit due to their simplified mechanical structure and feasibility for both low-speed and high-speed operations. Direct-torque control (DTC) is a classical control scheme that can be readily extended to LIMs. However, due to the high thrust ripple and poor dynamic performance for the low-speed operation, control performance of DTC is not satisfactory. This paper is to propose an explicit model predictive control to be combined with the DTC scheme. First, the LIM model is presented and discretized. Then, the LIM drive and its operating principle are discussed. Thirdly, the controller design, including control variables, and the objective function are depicted. Finally, both the simulation and the experiment are engaged for verifying the proposed control algorithm. [ABSTRACT FROM PUBLISHER]