CAD/CAM-based force controller using a neural network-based effective stiffness estimator

Nagata, Fusaomi; Mizobuchi, Takanori; Hase, Tetsuo; Haga, Zenku; Watanabe, Keigo; Habib, Maki K.

doi:10.1007/s10015-010-0776-9

Cited by 5 publications

(4 citation statements)

References 2 publications

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“…The following is the relationship between the displacement and force of the system in which the end of the robot is equipped with a wool ball polishing tool and a rubber abrasive polishing tool, where the angle is 45° between the surface normal vector and the base coordinate system. 18 Figure 5 shows the relationship between displacement and force where the robot is equipped with different polishing tools. Figure 6 indicates the relationship between displacement and stiffness with different polishing tools.…”

Section: Surface Polishing Strategymentioning

confidence: 99%

Research and application on force control of industrial robot polishing concave curved surfaces

Ding

Min

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part B:

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In order to improve the quality of the industrial robot automatic polishing on curved surfaces and ensure the constant polishing pressure during polishing process, a method for polishing complex concave cavity surfaces with industrial robot is proposed in this article. The method can achieve stable force control and precise position control and is easy to be realized online. In order to ensure the removal rate uniformity of surface material at different normal vectors, a method for adjusting the speed of motorized spindle in real time according to the surface normal vector is proposed. After planning the trajectory and normal vectors, combined with the feedback force signal from the sensor and the proportional–integral controller in the direction of the normal vector, the robot terminal tool corrects the trajectory in the direction of the surface normal vector, indirectly realizing force control between the tool and the surface. The robot polishing system with different polishing tools has different system stiffness. In order to ensure the polishing system with different stiffness to have a better tracking performance of the contact force, an adaptive proportional–integral control algorithm proposed in this article can be used to evaluate the stiffness of polishing system and to adjust proportional–integral parameters. The simulation and experimental results indicate that the method can realize the polishing of concave cavity surface commendably.

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Section: Surface Polishing Strategymentioning

confidence: 99%

Research and application on force control of industrial robot polishing concave curved surfaces

Ding

Min

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…Research into environmental stiffness and the influence of damping on the force/position control between the robot and the environment is the basis of using robot impedance control. [12][13] …”

Section: Robot Impedance Control Modelmentioning

confidence: 99%

A Study of Force and Position Tracking Control for Robot Contact with an Arbitrarily Inclined Plane

Song

et al. 2013

International Journal of Advanced Robotic Systems

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This paper proposes an adaptive impedance control method for a robot's end-effector while it slides steadily on an arbitrarily inclined panel; it concentrates on robot force position tracking control for the inclined plane with an unknown normal direction and varying environmental damping and stiffness. The proposed control strategy uses the Recursive Least Squares (RLS) algorithm to estimate environmental damping and stiffness parameters during the impact-contact process between the robot and the environment. It achieves the expected posture adjustment of the robot's end-effector based on the measured contact torques and, during the robot's endeffectorʹs sliding on the inclined plane, a fuzzy control is developed to adjust the robot impedance model parameters on-line and adaptively for changes in environmental damping and stiffness. The designed robot force position control method is robust to the changes of the environmental parameters but the implementation of the proposed control algorithms is simple. Finally, experiments demonstrate the effectiveness of the proposed method.

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“…Therefore, ways must be found for adjusting the stiffness and damping of the robot impedance model to accommodate environmental effective stiffness and damping varying in actual application. At present, one of the hot topics for robot impedance control is to improve the stability of contact force tracking control during robot-environment interaction, considered that environmental effective stiffness and damping are unknown or changing [8][9].…”

Section: Introductionmentioning

confidence: 99%

“…For example, Nagata F. employed records of the contact force and environmental stiffness from the robot-environment interaction to train the NN off-line, and the trained NN was used to estimate the environmental stiffness on-line, it established impedance model based force control adaptive to various environmental stiffness [9]. Mallapragada V. adopted the recorded displacement and contact force during the robot-environment interaction to train the NN, and the trained NN afforded the adjustment for the coefficients of the proportional-differential (PD) control according to different environments, it established the impedance model based force control [10].…”

Section: Introductionmentioning

confidence: 99%

Research of a Self-adaptive Robot Impedance Control Method for Robot-Environment Interaction

Yang

Zhou

et al. 2015

Advances in Intelligent Systems and Computing

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Abstract. The robot impedance control performance decreases with unknown or changing environmental stiffness and damping parameters, in order to resolve this problem, this paper designs a self-adaptive robot impedance control method, which is characterized by integration of off-line learning and on-line adjustment to afford the stiffness and damping of the robot control system's impedance model competent for unknown or changing environment. For the off-line learning, defining the robot impedance control performance criterion, and establishing the geometric representation of the varying stiffness parameter, we derive the initial values of stiffness for the impedance model. Further, a neural network is designed to estimate the environmental effective stiffness, and combined with critical damping condition of the second-order robot-environment interaction system, we solves the initial value of damping for the impedance model. During the on-line adjustment, a rule self-tuned fuzzy controller is dedicated to adjust the stiffness and damping of the impedance model based on robot real-time contact force and position feedback. At last, experiments demonstrate the excellent stability and accuracy for the robot-environment contact force tracking control.

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CAD/CAM-based force controller using a neural network-based effective stiffness estimator

Cited by 5 publications

References 2 publications

Research and application on force control of industrial robot polishing concave curved surfaces

Research and application on force control of industrial robot polishing concave curved surfaces

A Study of Force and Position Tracking Control for Robot Contact with an Arbitrarily Inclined Plane

Research of a Self-adaptive Robot Impedance Control Method for Robot-Environment Interaction

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