Augmented Image-Based Visual Servoing of a Manipulator Using Acceleration Command

Keshmiri, Mohammad; Xie, Wenfang; Mohebbi, Abolfazl

doi:10.1109/tie.2014.2300048

Cited by 80 publications

(59 citation statements)

References 19 publications

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“…This Figure shows how the controller takes the features to their desired value without any unnecessary motions. A similar test was performed in [7]. Comparing the results shows that considering the constraints in the controller could improve the trajectory of the features in image plane.…”

Section: Testmentioning

confidence: 94%

See 1 more Smart Citation

On–Line Model Predictive Control for Constrained Image Based Visual Servoing of a Manipulator

Hajiloo¹,

Keshmiri²,

Xie³

2015

2015 Proceedings of the Conference on Control and Its Applications

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This paper presents an on-line image based visual servoing (IBVS) controller for a 6 DOF robotic system based on the robust model predictive control (RMPC) method. The controller is designed considering the robotic visual servoing system's input and output constraints, such as robot physical limitations and visibility constraints. The proposed IBVS controller avoids the inverse of the image Jacobian matrix and hence can solve the intractable problems for the classical IBVS controller, such as large displacements between the initial and the desired positions of the camera. To verify the effectiveness of the proposed algorithm, real-time experimental results on a 6 Degrees-of-Freedom (DOF) robot manipulator with eye-in-hand configuration are presented and discussed.

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Section: Testmentioning

confidence: 94%

“…The visual servoing block uses a controlling command to generate a velocity screw as the control input for the robotic systems which leads to the desired joint velocity. The robot controller takes the signal produced by the visual servoing block as its desired path and the robot controller drives the robot to follow that path [7].…”

mentioning

confidence: 99%

On–Line Model Predictive Control for Constrained Image Based Visual Servoing of a Manipulator

Hajiloo¹,

Keshmiri²,

Xie³

2015

2015 Proceedings of the Conference on Control and Its Applications

Self Cite

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“…In [55], a new image-based visual servo controller was created for a 6-DOF gripper. The controller was able to achieve a more linear trajectory and reduced the risk of having image features leave the field of view.…”

Section: Grippers For Unknown Environmentsmentioning

confidence: 99%

State of the Art Robotic Grippers and Applications

et al. 2016

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Abstract:In this paper, we present a recent survey on robotic grippers. In many cases, modern grippers outperform their older counterparts which are now stronger, more repeatable, and faster. Technological advancements have also attributed to the development of gripping various objects. This includes soft fabrics, microelectromechanical systems, and synthetic sheets. In addition, newer materials are being used to improve functionality of grippers, which include piezoelectric, shape memory alloys, smart fluids, carbon fiber, and many more. This paper covers the very first robotic gripper to the newest developments in grasping methods. Unlike other survey papers, we focus on the applications of robotic grippers in industrial, medical, for fragile objects and soft fabrics grippers. We report on new advancements on grasping mechanisms and discuss their behavior for different purposes. Finally, we present the future trends of grippers in terms of flexibility and performance and their vital applications in emerging areas of robotic surgery, industrial assembly, space exploration, and micromanipulation. These advancements will provide a future outlook on the new trends in robotic grippers.

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“…Substituting the second‐order kinematics of the robot system and the low‐level control equation in the second‐order differential equation of the error given by Equation , the following equation is obtained:

bolde + K_{j 1} \overset{e}{true} + K_{j 2} \overset{e}{true} = bolde + K_{j 1} \overset{e}{true} + K_{j 2} ((), J_{s} false({\overset{q}{true}}_{c} + d_{c a} false) + {\overset{J}{true}}_{s} \overset{q}{true} + \partial \overset{e}{true} false/ \partial t) = bold0,

and the commanded joint acceleration vector results in

{\overset{q}{true}}_{c} = - {boldJ}_{s}^{†} ((), K_{j 2}^{- 1} bolde + K_{j 2}^{- 1} K_{j 1} \overset{e}{true} + {\overset{J}{true}}_{s} \overset{q}{true} + \partial \overset{e}{true} false/ \partial t) - d_{c a},

which represents the classical operational space robot control that has already been used in VS applications by Fakhry and Wilson for PBVS and by Keshmiri et al for IBVS.…”

Section: Comparison With Classical Continuous Controlmentioning

confidence: 99%

“…In this respect, we can find in the literature a vast number of approaches, eg, classic PID controllers() and optimal() and robust controllers,() based on learning. () However, other continuous approaches that are based on computing joint accelerations to be commanded to joint actuators can be found either in PBVS or in IBVS …”

Section: Introductionmentioning

confidence: 99%

Sliding mode control for robust and smooth reference tracking in robot visual servoing

Muñoz-Benavent

Gracia

Solanes

et al. 2017

Intl J Robust & Nonlinear

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An approach based on sliding mode is proposed in this work for reference tracking in robot visual servoing. In particular, 2 sliding mode controls are obtained depending on whether joint accelerations or joint jerks are considered as the discontinuous control action. Both sliding mode controls are extensively compared in a 3D-simulated environment with their equivalent well-known continuous controls, which can be found in the literature, to highlight their similarities and differences. The main advantages of the proposed method are smoothness, robustness, and low computational cost. The applicability and robustness of the proposed approach are substantiated by experimental results using a conventional 6R industrial manipulator (KUKA KR 6 R900 sixx [AGILUS]) for positioning and tracking tasks.

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Augmented Image-Based Visual Servoing of a Manipulator Using Acceleration Command

Cited by 80 publications

References 19 publications

On–Line Model Predictive Control for Constrained Image Based Visual Servoing of a Manipulator

On–Line Model Predictive Control for Constrained Image Based Visual Servoing of a Manipulator

State of the Art Robotic Grippers and Applications

Sliding mode control for robust and smooth reference tracking in robot visual servoing

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