Vision sensor based residual vibration suppression strategy of non-deformable object for robot-assisted assembly operation with gripper flexibility

Jalendra, Chetan; Rout, B.K.; Marathe, Amol

doi:10.1108/ir-09-2021-0197

Cited by 8 publications

(7 citation statements)

References 29 publications

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“…Recently, an active second-stage control strategy for vibration suppression was proposed that communicates with the robot’s internal controller without any modification (Jalendra and Rout, 2020). Consequently, the existing sensor is replaced with a vision sensor and converted contact to a non-contact sensor feedback system to suppress vibration of the non-deformable object grasped by a flexible gripper (Jalendra et al , 2020, 2022). These control methods were limited to applications on the object with a single degree of freedom (DoF) and the vision system was very object-specific and required exact alignment to measure the angular amplitude of the oscillating rigid object.…”

Section: Introductionmentioning

confidence: 99%

Robot vision-based control strategy to suppress residual vibration of a flexible beam for assembly

Jalendra

Rout²,

Marathe³

2022

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Purpose Industrial robots are extensively used in the robotic assembly of rigid objects, whereas the assembly of flexible objects using the same robot becomes cumbersome and challenging due to transient disturbance. The transient disturbance causes vibration in the flexible object during robotic manipulation and assembly. This is an important problem as the quick suppression of undesired vibrations reduces the cycle time and increases the efficiency of the assembly process. Thus, this study aims to propose a contactless robot vision-based real-time active vibration suppression approach to handle such a scenario. Design/methodology/approach A robot-assisted camera calibration method is developed to determine the extrinsic camera parameters with respect to the robot position. Thereafter, an innovative robot vision method is proposed to identify a flexible beam grasped by the robot gripper using a virtual marker and obtain the dimension, tip deflection as well as velocity of the same. To model the dynamic behaviour of the flexible beam, finite element method (FEM) is used. The measured dimensions, tip deflection and velocity of a flexible beam are fed to the FEM model to predict the maximum deflection. The difference between the maximum deflection and static deflection of the beam is used to compute the maximum error. Subsequently, the maximum error is used in the proposed predictive maximum error-based second-stage controller to send the control signal for vibration suppression. The control signal in form of trajectory is communicated to the industrial robot controller that accommodates various types of delays present in the system. Findings The effectiveness and robustness of the proposed controller have been validated using simulation and experimental implementation on an Asea Brown Boveri make IRB 1410 industrial robot with a standard low frame rate camera sensor. In this experiment, two metallic flexible beams of different dimensions with the same material properties have been considered. The robot vision method measures the dimension within an acceptable error limit i.e. ±3%. The controller can suppress vibration amplitude up to approximately 97% in an average time of 4.2 s and reduces the stability time up to approximately 93% while comparing with control and without control suppression time. The vibration suppression performance is also compared with the results of classical control method and some recent results available in literature. Originality/value The important contributions of the current work are the following: an innovative robot-assisted camera calibration method is proposed to determine the extrinsic camera parameters that eliminate the need for any reference such as a checkerboard, robotic assembly, vibration suppression, second-stage controller, camera calibration, flexible beam and robot vision; an approach for robot vision method is developed to identify the object using a virtual marker and measure its dimension grasped by the robot gripper accommodating perspective view; the developed robot vision-based controller works along with FEM model of the flexible beam to predict the tip position and helps in handling different dimensions and material types; an approach has been proposed to handle different types of delays that are part of implementation for effective suppression of vibration; proposed method uses a low frame rate and low-cost camera for the second-stage controller and the controller does not interfere with the internal controller of the industrial robot.

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Section: Introductionmentioning

confidence: 99%

Robot vision-based control strategy to suppress residual vibration of a flexible beam for assembly

Jalendra

Rout²,

Marathe³

2022

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“…The robot vision system communicates using socket programing, following a client-server model approach. 21 Experimental implementation of second stage controller Robot vision systems for vibration measurement commonly face motion blur due to low sensor sampling rates and fast-moving objects. Mounting the sensor at an inclined angle improves visibility of the tip and enables effective tracking.…”

Section: Details Of the Experimental Setupmentioning

confidence: 99%

“…The robot vision system communicates using socket programing, following a client-server model approach. 21…”

Section: Implementation Of Pmeb Controllermentioning

confidence: 99%

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Vision based control strategy to suppress residual vibration of flexible beams for robotic assembly using wrist motion

Jalendra,

Rout

2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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Automated assembly tasks require industrial robots to improve the efficiency of the manufacturing process. Most rigid or flexible objects handled by robots vibrate due to motion and transient disturbance. This work proposes an active vision-based vibration suppression strategy for flexible beams by providing motion to the wrist of a robot during robotic assembly process, which reduces the time to suppress vibration. The proposed method uses a cheap monocular camera to identify objects through a virtual marker and measure their dimensions. Subsequently, finite element method based mathematical model of a flexible beam predicts the maximum error. The proposed second stage controller determines the controller input in terms of wrist motion based on the predicted maximum error. The performance of the controller is assessed through simulations and experiments on metallic beams with different material characteristics and dimensions. The controller suppresses vibration amplitude within a safe limit so that object is inserted into the slot. It was observed from experiments that the controller can reduce vibration amplitude by ~96% in less than 2 s and decrease suppression time up to ~97%. These improvements were achieved without disturbing the internal robot controller.

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“…By establishing a flexible dynamic model of the robot, trajectory planning can be carried out based on spline curves and polynomial curves with the excitation force as the optimization goal; however, such a model is appropriate for single-degree-of-freedom or planar robots [22][23][24][25]. A vision-based noncontact vibration suppression method was proposed based on the vibration amplitude error prediction model, and an error estimation controller was designed so that the vibration could be controlled in real time [26]. However, this study only focused on vibration suppression, and the factors influencing the vibration behaviour were not revealed.…”

Section: Introductionmentioning

confidence: 99%

Vibration Behaviour Analysis and Vibration Suppression Studies of the Space Robot

Tian

Yue

Feng

et al. 2022

International Journal of Aerospace Engineering

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Aiming at the problem that the vibration of space robot will reduce the dynamic accuracy of robot, a method of vibration suppression of space robot through trajectory planning is proposed. First, the joint was simplified to a linear torsion spring, and the flexible rod was modelled using the finite element method, resulting in a flexible motion model of the robot. Then, a rigid-soft coupled dynamic model that combined the flexible motion model with the Lagrange method was established. Using the dynamic model, the factors influencing the vibration behaviour of space robots were analysed. Finally, the space robot was subjected to vibration suppression through trajectory planning. As verified by experimental analysis, different trajectories and loads affect the excitation force and inherent characteristics of the robot. In the design process, it is necessary to consider the relationship between the excitation force and natural frequency. The trajectory planning method has apparent effects on vibration suppression. The vibration amplitude was significantly reduced, which can improve the positioning accuracy and work efficiency of the robot.

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Vision sensor based residual vibration suppression strategy of non-deformable object for robot-assisted assembly operation with gripper flexibility

Cited by 8 publications

References 29 publications

Robot vision-based control strategy to suppress residual vibration of a flexible beam for assembly

Robot vision-based control strategy to suppress residual vibration of a flexible beam for assembly

Vision based control strategy to suppress residual vibration of flexible beams for robotic assembly using wrist motion

Vibration Behaviour Analysis and Vibration Suppression Studies of the Space Robot

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