Stiffness-oriented posture optimization in robotic machining applications

Guo, Yingjie; Dong, Huiyue; Ke, Yinglin

doi:10.1016/j.rcim.2015.02.006

Cited by 207 publications

(80 citation statements)

References 14 publications

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“…Xiong et al proposed a discrete search algorithm for the operation configuration of milling robot with optimal stiffness performance, and the optimization results significantly improved the trajectory accuracy [12]. Guo et al took the robot stiffness ellipsoid as the stiffness evaluation index to improve the robot stiffness by configuration optimization, and obtained accuracy of higher drilling axial and countersink depth [13]. However, these studies focus on configuration optimization for processing tasks with discrete positions.…”

Section: Introductionmentioning

confidence: 99%

Variable stiffness identification and configuration optimization of industrial robots for machining tasks

Jiao¹,

Tian²,

Zhang³

et al. 2020

Preprint

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Industrial robots are increasingly used in machining tasks because of their high flexibility and intelligence. However, the low structural stiffness of the robot seriously affects the positional accuracy and machining quality of robot operation equipment. Studying robot stiffness characteristics and optimization methods is an effective way to improve robot stiffness performance. Accordingly, aiming at the poor accuracy of stiffness modeling caused by approximating stiffness of each joint as constant, a variable stiffness identification method is proposed based on space gridding. Then, a task-oriented axial stiffness evaluation index is proposed to realize quantitative assessment of the stiffness performance in the machining direction. Besides, by analyzing the redundant kinematic characteristics of the robot machining system, a configuration optimization method is further come up with to maximize the index. For a large number of points or trajectory processing tasks, a configuration smoothing strategy is proposed to achieve fast acquisition of optimized configurations. Finally, experiments on a KR500 robot are conducted to verify the feasibility and validity of proposed stiffness identification and configuration optimization methods.

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Section: Introductionmentioning

confidence: 99%

Variable stiffness identification and configuration optimization of industrial robots for machining tasks

Jiao¹,

Tian²,

Zhang³

et al. 2020

Preprint

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“…The configuration of the robot and the cutting force acting on it during machining are dependent upon the pose of the workpiece relative to the robot. It has been found that the natural frequencies of a robot strongly depend on its configuration [34] and that the robot stiffness varies significantly in different directions [35,36] and can be improved by optimizing the robot configuration for a given pick-and-place task [36][37][38], which implies that the vibration characteristics of robotic machining are affected by how the workpiece is placed with respect to the robot. For example, the robot stiffness is considered in Reference [37] for the optimization of the redundant degrees of freedom to minimize the displacement of the cutting tool under static force.…”

Section: Introductionmentioning

confidence: 99%

Workpiece Pose Optimization for Milling with Flexible-Joint Robots to Improve Quasi-Static Performance

Qin

Xiong

2019

Applied Sciences

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Although industrial robots are widely used in production automation, their applications in machining have been limited because of the structural vibrations induced by periodic cutting forces. Since the dynamic characteristics of an industrial robot depends on its configuration, the responses of the robot structure to the cutting forces are affected by how the workpiece is placed within the workspace of the robot. This paper presents a method for workpiece pose optimization for a robotic milling system to improve the quasi-static performance during machining. Since the milling forces are time-varying due to the characteristics of the multi-tooth and discontinuity of milling, these forces can excite vibrations inside the robot structure. To address this issue, a structural dynamics model is established for industrial robots, considering their joint flexibility, and a milling force formulation is incorporated into the robot dynamics model to investigate the forced vibrations of the flexible joints. Then, the quasi-static performance of the robotic machining system is evaluated by the vibration-induced offset of the cutter tool that is mounted on the end-effector. Finally, an optimization approach is given for the workpiece pose to minimize the cutter tool offset under the periodic milling force. A numerical simulation demonstrates that the optimal workpiece pose can significantly reduce the overall tool offset during machining and can lower the variation of the tool offset along the milling path.

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“…Before the machining process, cutting tests at different spindle speeds are carried out, and the spindle speed which has the lowest RMS directional value will be implemented for robotic milling. Guo et al 14 presented an optimization method for robot postures in machining applications, which can be used to find the robot posture that has the largest stiffness at a certain tool center location. By optimizing the robot postures at different tool center locations along the machining path, the robot stiffness and the chatter stability can be improved.…”

Section: Introductionmentioning

confidence: 99%

Design of eddy current dampers for vibration suppression in robotic milling

Fan

Zhao

2018

Advances in Mechanical Engineering

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The milling robot normally has a low stiffness which may easily cause chatter during machining. This article presents a novel eddy current damper design for chatter suppression in the robotic milling process. The designed eddy current dampers are installed on the milling spindle to damp the tool tip vibrations. The structural design and the working principle of the eddy current dampers are explained. The magnetic flux density distribution and the magnetic force generation of the designed eddy current damper are analyzed with the finite element method. The tool tip dynamics without and with eddy current dampers are modeled, and the damping performance of the proposed eddy current dampers in the robotic milling process is verified through both simulations and experiments. The results show that the peaks of the tool tip frequency response function caused by the milling tool modes are damped significantly, and the stable depth of cut is improved greatly with eddy current dampers.

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Stiffness-oriented posture optimization in robotic machining applications

Cited by 207 publications

References 14 publications

Variable stiffness identification and configuration optimization of industrial robots for machining tasks

Variable stiffness identification and configuration optimization of industrial robots for machining tasks

Workpiece Pose Optimization for Milling with Flexible-Joint Robots to Improve Quasi-Static Performance

Design of eddy current dampers for vibration suppression in robotic milling

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