Robust fulfillment of constraints in robot visual servoing

Muñoz-Benavent, Pau; Gracia, Luis; Solanes, J. Ernesto; Esparza, Alicia; Tornero, Josep

doi:10.1016/j.conengprac.2017.10.017

Cited by 7 publications

(6 citation statements)

References 49 publications

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“…The main limitation of the proposed ASMC method is the chattering drawback, although it is partially mitigated in this work introducing a firstorder low-pass filter between the original constraint function σ i and the modified constraint function φ i , see (18) and (19). Therefore, although φ i theoretically switches its value every sampling period, the original constraint function σ i is significantly smoothed, see Fig.…”

Section: Advantages and Limitations Of The Proposed Methodsmentioning

confidence: 99%

“…The proposed method is based on satisfying a set of constraints to properly perform the desired surface contact conditioning. In this sense, the authors previously presented in [17] a conventional SMC to fulfill equality constraints, whereas in [18] developed a non-conventional SMC to fulfill inequality constraints. In both cases, however, the control application was focused on robot visual servoing.…”

Section: Introductionmentioning

confidence: 99%

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Adaptive robust control and admittance control for contact-driven robotic surface conditioning

Solanes

Gracia

Muñoz-Benavent

et al. 2018

Robotics and Computer-Integrated Manufacturing

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This work presents a hybrid position/force control of robots for surface contact conditioning tasks such as polishing, profiling, deburring, etc. The robot force control is designed using sliding mode ideas to benefit from robustness. On the one hand, a set of equality constraints are defined to attain the desired tool pressure on the surface, as well as to keep the tool orientation perpendicular to the surface. On the other hand, inequality constraints are defined to adapt the tool position to unmodeled features present in the surface, e.g., a protruding window frame. Conventional and non-conventional sliding mode controls are used to fulfill the equality and inequality constraints, respectively. Furthermore, in order to deal with sudden changes of the material stiffness, which are forwarded to the robot tool and can produce instability and bad performance, adaptive switching gain laws are considered not only for the conventional sliding mode control but also for the non-conventional sliding mode control. A lower priority tracking controller is also defined to follow the desired reference trajectory on the target surface. Moreover, the classical admittance control typically used in force control tasks is adapted for the proposed surface contact application in order to experimentally compare the performance of both control approaches. The effectiveness of the proposed method is substantiated by experimental results using a redundant 7R manipulator, whereas its advantages over the classical admittance control approach are experimentally shown.

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Section: Advantages and Limitations Of The Proposed Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Adaptive robust control and admittance control for contact-driven robotic surface conditioning

Solanes

Gracia

Muñoz-Benavent

et al. 2018

Robotics and Computer-Integrated Manufacturing

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“…By combining different visual servo structures or designing a new VS structure, the object is always in the camera FOV, such as combining IBVS and PBVS approach, 21 switching approach, 22 zooming VS approach, 23 direct VS approach, 24 and IBVS with a Kalman-neural-network filtering approach. 25 Besides, some advanced control laws are designed to deal with the FOV constraint problem, such as sliding mode control, 26,27 model predictive control, [28][29][30] prescribed performance control, 31,32 switched controller, 6,33 and so on. Furthermore, some proposals are relying on robot-camera configuration, such as multicamera scheme, 34 the light field camera scheme, 35 and so on.…”

Section: Introductionmentioning

confidence: 99%

Visual servoing of robot manipulator with weak field-of-view constraints

Xin¹,

Han²,

Bao-jing³

2021

International Journal of Advanced Robotic Systems

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Aiming at the problem of servoing task failure caused by the manipulated object deviating from the camera field-of-view (FOV) during the robot manipulator visual servoing (VS) process, a new VS method based on an improved tracking learning detection (TLD) algorithm is proposed in this article, which allows the manipulated object to deviate from the camera FOV in several continuous frames and maintains the smoothness of the robot manipulator motion during VS. Firstly, to implement the robot manipulator visual object tracking task with strong robustness under the weak FOV constraints, an improved TLD algorithm is proposed. Then, the algorithm is used to extract the image features (object in the camera FOV) or predict image features (object out of the camera FOV) of the manipulated object in the current frame. And then, the position of the manipulated object in the current image is further estimated. Finally, the visual sliding mode control law is designed according to the image feature errors to control the motion of the robot manipulator so as to complete the visual tracking task of the robot manipulator to the manipulated object in complex natural scenes with high robustness. Several robot manipulator VS experiments were conducted on a six-degrees-of-freedom MOTOMANSV3 industrial manipulator under different natural scenes. The experimental results show that the proposed robot manipulator VS method can relax the FOV constraint requirements on real-time visibility of manipulated object and effectively solve the problem of servoing task failure caused by the object deviating from the camera FOV during the VS.

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“…Chaumette (2002Chaumette ( , 2004 and Tahri et al (2015) proposed the use of image moments due to their ability to represent object regions, although the rotational motions around the X-and Y-axes simultaneously with the translational motions along the same axes remain a key issue. Other approaches are focused on introducing image or joint constraints in order to avoid reaching the joint limits (Marchand, Rizzo, and Chaumette (1996); Han and Park (2013)) or the loss of the visual features vector (Muñoz-Benavent et al (2018); Qiu, Hu, and Liang (2019)). A different approach was presented in Solanes et al (2013), which used the duality of LQRlike controllers (Armesto et al (2015)) and an Extended Kalman Filter Smoother (Todorov (2005(Todorov ( , 2008; Zima et al (2013)) to develop a novel Reference Filtering Control Strategy (RFCS) able to significantly increase the solution reachability of the classic Image Based Visual Servoing (IBVS) controller.…”

Section: Introductionmentioning

confidence: 99%

Generalization of reference filtering control strategy for 2D/3D visual feedback control of industrial robot manipulators

Solanes

Muñoz-Benavent

Armesto

et al. 2021

International Journal of Computer Integrated Manufacturing

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This paper develops the application of the Dual Rate Dual Sampling Reference Filtering Control Strategy to 2D and 3D visual feedback control. This strategy allows to overcome the problem of sensor latency and to address the problem of control task failure due to visual features leaving the camera field of view. In particular, a Dual Rate Kalman Filter is used to generate inter-sample estimations of the visual features to deal with the problem of vision sensor latency, whereas a Dual Rate Extended Kalman Filter Smoother is used to generate more convenient visual features trajectories in the image plane. Both 2D and 3D visual feedback control approaches are widely analyzed throughout the paper, as well as the overall system performance using different visual feedback controllers, providing a set of results that highlight the improvements in terms of solution reachability, robustness, and time domain response. The proposed control strategy has been validated on an industrial system with hard real-time limitations, consisting of a 6 DOF industrial manipulator, a 5 MP camera, and a PLC as controller.

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Robust fulfillment of constraints in robot visual servoing

Cited by 7 publications

References 49 publications

Adaptive robust control and admittance control for contact-driven robotic surface conditioning

Adaptive robust control and admittance control for contact-driven robotic surface conditioning

Visual servoing of robot manipulator with weak field-of-view constraints

Generalization of reference filtering control strategy for 2D/3D visual feedback control of industrial robot manipulators

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