Chen, CS & Chen, SK 2019, 'Synchronization of tool tip trajectory and attitude based on the surface characteristics of workpiece for 6-DOF robot manipulator', Robotics and Computer-Integrated Manufacturing, vol. 59, pp. 13-27.View/Download from: Publisher's site
© 2019 This study proposes a method to extract feature points from the surface characteristics according to the machining accuracy of a 6-Degrees-of-Freedom (6-DOF) robot manipulator, which makes the fitting of the B-spline curve easier and decreases the amount of calculation for the approximation process. The tool tip trajectory is defined via B-spline curve fitting. Many robotic controllers use two Non-Uniform Rational B-Spline (NURBS) curves to represent the trajectories of the tool tip and tool axis but these double trajectories are not synchronous. In order to synchronize the orientation with the tool tip trajectory, this study uses a rotation matrix and a machining direction vector to plan the attitude of the tool. Before the attitude is planned, interpolation is used to generate the motion command for the tool tip using the S-Curve feedrate profile. The trajectory of the tool tip is further used to calculate the synchronized tool reference using a rotation transformation. Finally, the tool tip trajectory and the corresponding synchronized tool reference are used to determine the machining position and the orientation information. One of the experimental results shows that the proposed method can simultaneously sustain a 10 μm machining accuracy with a significant decrease in the computation load from 1113 s to 31 s.
Chen, CS, Chen, SK & Chen, LY 2019, 'Disturbance Observer-Based Modeling and Parameter Identification for Synchronous Dual-Drive Ball Screw Gantry Stage', IEEE/ASME Transactions on Mechatronics, vol. 24, no. 6, pp. 2839-2849.View/Download from: Publisher's site
© 1996-2012 IEEE. A novel algorithm is proposed to identify the parameters of a synchronous dual-drive ball screw gantry system in this paper. The modeling of the gantry system is described in this paper, and dynamic equations are used to derive the relationship from the motor to the coupling mechanism. The modeling results are used to design the algorithm used to identify the model parameters. The proposed algorithm uses two disturbance observers (DOB) to identify the parameters for the coupling mechanism and sliding stages. The sinusoidal position and velocity commands for the proposed identification algorithm are relatively smooth to avoid damaging the mechanism. The proposed method is easy to implement in the position control loop and velocity control loop. Finally, simulation and experimental results show that the proposed DOBs can accurately estimate the parameters for a gantry system, and the estimated results can be further used to design a corresponding controller for the gantry stage.
Chen, CS, Hsu, CY, Chen, SK, Lin, CJ, Hsieh, CH & Liu, YH 2017, 'Image correction for cone-beam computed tomography simulator using neural network corrector', Advances in Mechanical Engineering, vol. 9, no. 2.View/Download from: Publisher's site
© The Author(s) 2017. In this article, a neural network corrector is proposed to correct the image shift, yielding the degradation of three-dimensional image reconstruction, for each slice captured by cone-beam computed tomography simulator. There are 3 degrees of freedom in tube module of simulator; the central point of tube module should be aligned with the central point of detector module to guarantee the accurate image projection. However, the mechanism manufacturing and assembling tolerance will let the above aim cannot be met. Here, a standard kit is made to measure the image shift by 1 ° step from 10° to 10°. The measure data will be the input training data of proposed neural network corrector, and the corrected translation position will be the output of neural network corrector. The Levenberg-Marquardt learning algorithm adjusts the connected weights and biases of the neural network using a supervised gradient descent method, such that the defined error function can be minimized. To avoid the problem of overfitting and improve the generalized ability of the neural network, Bayesian regularization is added to the Levenberg-Marquardt learning algorithm. After the training of neural network corrector, the different target position commands are fed into the neural network corrector. Then, the corrected data from neural network corrector are fed to be the new position command to verify the image correction performance. Moreover, a phantom kit is made to check the corrected performance of the neural network corrector. Finally, the experimental results verify that the image shift can be reduced by the neural network corrector.
Chen, SK & Chen, CS 2019, 'Motion Primitive Recognition on Human Guided Robotic Arm using Machine Learning', International Conference on Control, Automation and Systems, International Conference on Control, Automation and Systems, IEEE, Jeju, Korea (South), pp. 955-960.View/Download from: Publisher's site
© 2019 Institute of Control, Robotics and Systems - ICROS. This paper proposed a novel intuitive teaching technologies by reconstructing the recorded motion information during human guided robotic arm. A learning algorithm is proposed in this paper to recognize the motion primitives according to therbligs definition. The hybrid sensing interface is used to record and modified the positional trajectory, force/torque, and gripper information. Furthermore, an extended Kalman filter is used to pre-process the data and estimate the velocity and acceleration profile as motion features. The motion features, output data via the hybrid sensing interface, is finally used to recognize the target therblig by proposed cascade support vector machine. The experimental results show that the proposed method can recognize the motion features into therbligs correctly and efficiently. The recognition results can be further used to reconstruct an assembly operation.
Chen, CS, Liu, SB & Chen, SK 2018, 'Smooth path planning for intuitive teaching of 6-DOF manipulator tasks', International Conference on Advanced Robotics and Intelligent Systems, ARIS.View/Download from: Publisher's site
© 2017 IEEE. This paper proposed a skill to smooth the trajectory for intuitive teaching of 6-DOF manipulator tasks. Firstly, the teaching zones, including the starting zone and ending zone, and safety zone are well defined for different applications. Then, the backtracking method is used to teach the corresponding tasks in the ending zone to guarantee the accurate positioning of target point. In addition, a cubic spline is applied to connect two discrete points which are the boundary of teaching zone. The proposed strategy make the intuitive teaching more efficient in the teaching process and more accurate in the target position.
© 2016 ACM. This paper proposes a solution of collision avoidance path planning for the 6-degree of freedom (6-DOF) robotic manipulator based on the virtualized platform. It can effectively avoid danger by consider the planned path whether collide with other modules through the digital simulation. This technology includes: (1) collision detection, (2) avoidance path planning. The models of existing obstacles and 6-DOF robotic manipulator in the work-space are firstly created. The collision detection is further realized through the created models. Then, an optimal avoidance path is obtained by the rapidly-exploring random tree (RRT) algorithm, but it involves many redundant vertexes. This paper proposes the Reduce Vertex RRT algorithm (RVRRT) to decrease the redundant vertex. Therefore, the collision avoidance path can increase the productivity when the 6-DOF robotic manipulator is applied in the production line.
Chen, CS, Chen, SK & Lai, CH 2015, 'Real-time coplanar NURBS curve fitting and interpolation for 6-DOF robot arm', 2015 International Conference on Advanced Robotics and Intelligent Systems, ARIS 2015.View/Download from: Publisher's site
© 2015 IEEE. This paper proposes a real-time coplanar Non-Uniform Rational B-Spline (NURBS) curves fitting and interpolation for 6-DOF robot arm to improve the fitting and interpolation quality, and reduce the calculation effort. The process consists of (1) reading discrete points, (2) discrete points extraction, (3) curve fitting, (4) interpolation, and (5) inverse kinematics transformation. According to the simulation and experimental results, the proposed approach certainly raises the fitting and interpolation quality, and the efficiency of calculation.