Vision-based Control of a Delta Parallel Robot via Linear Camera-Space Manipulation

Coronado, Enrique; Maya, Mauro; Cárdenas, Antonio; Guarneros, O.; Piovesan, Davide

doi:10.1007/s10846-016-0413-5

Cited by 26 publications

(20 citation statements)

References 28 publications

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“…Recently, the real-time vision-based control, the analysis and the real-time trajectory tracking control validated on a real parallel robots, e.g. [45][46][47] , have attracted more interests. In the kinematic modeling of the Par4 robot shown in Table V, one needs to estimate points A 1 1i .…”

Section: Resultsmentioning

confidence: 99%

Contribution to generic modeling and vision-based control of a broad class of fully parallel robots

2018

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SUMMARYThis paper deals with a generic modeling and vision-based control approach for a broad class of parallel mechanisms. First, a generic architecture representing several families is proposed. Second, inspired by the geometry of lines, a generic differential inverse kinematic model according to the proposed generic structure is introduced. Finally, based on the image projection of cylindrical legs, a kinematic vision-based control using legs observation is presented. The approach is illustrated and validated on the Gough–Stewart and Par4 parallel robots.

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Section: Resultsmentioning

confidence: 99%

Contribution to generic modeling and vision-based control of a broad class of fully parallel robots

2018

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“…The forward kinematic model (FKM) for the Delta Parallel robot is known and has been previously reported by Maya et al 47 and Coronado et al, 36 as well as the references therein. The FKM of this mechanism is based on a set of three closed chains which can be solved as the intersection of three spheres with radius L2 (15) with radius L2 and centered in (X i , Y i .…”

Section: Forward Kinematic Modelmentioning

confidence: 99%

“…More recently, the CSM has proven its value for the control of parallel robots. 36 This work utilized an academic prototype to provide a proof of concept and reported an average positioning error of 3.17 + 1.14 mm. Still work has to be done in order to make the most of the intrinsic advantages of an industrial parallel robot.…”

Section: Introductionmentioning

confidence: 99%

Estimation of camera-space manipulation parameters by means of an extended Kalman filter: Applications to parallel robots

González¹,

González-Galván²,

Maya³

et al. 2019

International Journal of Advanced Robotic Systems

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Parallel robots have a growing range of applications due to their appealing characteristics (high speed and acceleration, increased rigidity, etc.). However, several open problems make it difficult to model and control them. Low computational-cost algorithms are needed for high speed tasks where high accelerations are required. This article develops the nonlinear camera-space manipulation method and makes use of an extended Kalman filter (EKF) for the estimation of the camera-space manipulation parameters. This is presented as an alternative to the traditional method which can be time consuming while reaching convergence. The proposed camera-space manipulation parameter identification was performed in positioning tasks for a parallel manipulator and the experimental results are reported. Results show that it is possible to estimate the set of camera-space manipulation parameters by means of an extended Kalman filter. Using the proposed Kalman filter method we observed a significant reduction of the computational effort when estimating the camera-space manipulation parameters. However, there was no significant reduction of the robot’s positioning error. The proposed extended Kalman filter implementation requires only 2 ms to update the camera-space manipulation parameters compared to the 85 ms required by the traditional camera-space manipulation algorithm. Such time reduction is beneficial for the implementation of the method for a wide range of high speed and industrial applications. This article presents a novel use of an extended Kalman filter for the real-time estimation of the camera-space manipulation parameters and shows that it can be used to increase the positioning accuracy of a parallel robot.

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“…Nowadays, video cameras are widely used for navigation [35] as they provide signals that are a function of the position of the robot in its environment, thus, not presenting a cumulative error. Moreover, they are low cost, easy to implement, and several tools for image processing and analysis are available [36][37][38]. Vision-based control techniques have also been widely applied to control manipulators for the ease of controlling the relative position of the robot with respect to other objects in motion [39].…”

Section: Introductionmentioning

confidence: 99%

Vision-Based Control of a Mobile Manipulator With an Adaptable-Passive Suspension for Unstructured Environments

Cárdenas

Quiroz

Hernandez

et al. 2021

Journal of Mechanisms and Robotics

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The kinematic design and navigation control of a new autonomous mobile manipulator for uneven terrain is presented in this work. An innovative suspension system's design is based on the kinematic synthesis of an adaptable, passive mechanism that compensates for irregularities in the terrain and facilitate the control of the robotic platform using cameras. The proposed mobile robot suspension consists of two pairs of bogies joined by a crank-slider mechanism that allows the robot to adapt to the terrain irregularities. The mobile robot is also equipped with a robotic manipulator, of which a synthesis, simulation, and experimental validation are presented while manipulation is accomplished during movements on rough terrain. The proposed mobile robot has been fabricated using additive manufacturing (AM) techniques. A linear camera space manipulation (LCSM) control system has been developed and implemented to conduct experimental tests along uneven terrain. This mobile manipulator has been designed to transverse uneven terrain so that the loading platform is kept horizontal while crossing obstacles up to one-third of the size of its wheels. This feature allows the onboard cameras to stay oriented towards the target. The vision-based paradigm that enables the control of this mobile manipulator allows to estimate the position and orientation of its end effector and update the trajectory of the manipulator along the path towards the target. The experiments show a final precision for engagement of a pallet within +/− 2.5 mm in position and +/− 2 degrees in orientation.

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Vision-based Control of a Delta Parallel Robot via Linear Camera-Space Manipulation

Cited by 26 publications

References 28 publications

Contribution to generic modeling and vision-based control of a broad class of fully parallel robots

Contribution to generic modeling and vision-based control of a broad class of fully parallel robots

Estimation of camera-space manipulation parameters by means of an extended Kalman filter: Applications to parallel robots

Vision-Based Control of a Mobile Manipulator With an Adaptable-Passive Suspension for Unstructured Environments

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