Modeling and control of robotic automatic polishing for curved surfaces

Tian, Fuqiang; Lv, Chong; Li, Zhenguo; Liu, Guangbao

doi:10.1016/j.cirpj.2016.05.010

Cited by 125 publications

(54 citation statements)

References 21 publications

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“…With these requirements, bush trimming also has similarities to other robotic tasks that deal with soft or flexible objects, such as grasping agricultural produce (Henten, Slot, Hol, & Willigenburg, 2009;Li, Li, Yang, & Wang, 2013;Zhang et al, 2018), or destructive manipulation, like grinding or cutting surfaces (Andersson & Johansson, 2001;Lipton, Manchester, & Rus, 2017;Mohsin, He, Cai, Chen, & Du, 2017;Tian, Lv, Li, & Liu, 2016). Still, bush trimming has some specific properties that demand special attention in the path planning.…”

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confidence: 99%

Coverage trajectory planning for a bush trimming robot arm

Kaljaca

Vroegindeweij

Henten

2019

Journal of Field Robotics

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A novel motion planning algorithm for robotic bush trimming is presented. The algorithm is based on an optimal route search over a graph. Differently from other works in robotic surface coverage, it entails both accuracy in the surface sweeping task and smoothness in the motion of the robot arm. The proposed method requires the selection of a custom objective function in the joint space for optimal node traversal scheduling, as well as a kinematically constrained time interpolation. The algorithm was tested in simulation using a model of the Jaco arm and three target bush shapes. Analysis of the simulated motions showed how, differently from classical coverage techniques, the proposed algorithm is able to ensure high tool positioning accuracy while avoiding excessive arm motion jerkiness. It was reported that forbidding manipulation posture changes during the cutting phase of the motion is a key element for task accuracy, leading to a decrease of the tool positioning error up to 90%. Furthermore, the algorithm was validated in a real‐world trimming scenario with boxwood bushes. A target of 20 mm accuracy was proposed for a trimming result to be considered successful. Results showed that on average 82% of the bush surface was affected by trimming, and 51% of the trimmed surface was cut within the desired level of accuracy. Despite the fact that the trimming accuracy turned out to be lower than the stated requirements, it was found out this was mainly a consequence of the inaccurate, early stage vision system employed to compute the target trimming surface. By contrast, the trimming motion planning algorithm generated trajectories that smoothly followed their input target and allowed effective branch cutting.

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mentioning

confidence: 99%

Coverage trajectory planning for a bush trimming robot arm

Kaljaca

Vroegindeweij

Henten

2019

Journal of Field Robotics

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“…The number of industrial applications, in which robots come in contact with the environment and where it has a significant influence on the robotised processes realisation quality, is constantly increasing ( Mendes and Neto, 2015). The aforementioned processes include, among others, robotised mechanical processing such as grinding (Zhu et al, 2015), polishing (Gracia et al, 2018;Tian et al, 2016), or edge deburring (Burghardt et al, 2017b). Therefore, modelling and control of robots in interaction with the environment becomes crucial, particularly if the actual features of the environment are taken into account, such as flexibility or damping.…”

Section: Introductionmentioning

confidence: 99%

Position/Force Control of Manipulator in Contact with Flexible Environment

Gierlak

2019

Acta Mechanica Et Automatica

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The paper presents the issue position/force control of a manipulator in contact with the flexible environment. It consists of the realisation of manipulator end-effector motion on the environment surface with the simultaneous appliance of desired pressure on the surface. The paper considers the case of a flexible environment when its deformation occurs under the pressure, which has a significant influence on the control purpose realisation. The article presents the model of the controlled system and the problem of tracking control with the use of neural networks. The control algorithm includes contact surface flexibility in order to improve control quality. The article presents the results of numerical simulations, which indicate the correctness of the applied control law.

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“…For example, in the case of too large external disturbance, the convergence speed is slow, especially for the constant force control in the applications such as grinding processing, which may lead to large uctuations of the contact force. In recent years, scholars have proposed many force control methods that integrate both the classic methods and the intelligent algorithms, such as fuzzy control and neural network control [3][4][5][6][7][8][9]. Panwar and Sukavanam et al [4] used a feedforward neural network to compensate the uncertainty of the robot model and presented an optimized force/position hybrid control method.…”

Section: Introductionmentioning

confidence: 99%

“…e force/position hybrid control improved the control performance when the material sti ness changes during the processing. Tian et al [9] designed an antisaturation integral separation fuzzy PI controller with explicit force input and used the proposed controller to control the normal polishing force of curved surface workpieces in the process of an overall uniform mirror surface.…”

Section: Introductionmentioning

confidence: 99%

Disturbance Observer‐Based Robot End Constant Contact Force‐Tracking Control

Liang

2019

Complexity

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A disturbance observer-based hybrid sliding mode impedance control method is proposed in this paper, which is able to achieve robot end constant contact force-tracking control without force/torque sensors. The method requires only the values of joint torque, joint angle, and joint angular velocity, which are converted by robot servo motor signals, to implement the control. The control scheme consists of two parts: one is a disturbance observer and the other is a hybrid sliding mode impedance controller. The disturbance observer, which takes robot internal signals mentioned above as the inputs to estimate the robot end contact force, is designed based on generalized momentum, thus improving the estimation accuracy. The hybrid sliding mode impedance controller, which uses the values estimated by the disturbance observer and the robot internal signals as the inputs to calculate the corresponding position adjustment, integrates both the impedance control and sliding mode control, thus improving the force-tracking performance and robustness. Experimental results show that the proposed disturbance observer-based hybrid sliding mode impedance control method possesses high control precision.

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Modeling and control of robotic automatic polishing for curved surfaces

Cited by 125 publications

References 21 publications

Coverage trajectory planning for a bush trimming robot arm

Coverage trajectory planning for a bush trimming robot arm

Position/Force Control of Manipulator in Contact with Flexible Environment

Disturbance Observer‐Based Robot End Constant Contact Force‐Tracking Control

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