Visual servoing for the Robotenis system: A strategy for a 3 DOF parallel robot to hit a Ping-Pong ball

Traslosheros, A.; Sebastián, J.M.; Ángel, Leopoldo Armesto; Robertí, Flavio; Carelli, Ricardo

doi:10.1109/cdc.2011.6161242

Cited by 3 publications

(1 citation statement)

References 14 publications

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“…The Kalman Filter (KF) is a Bayesian estimation technique used to observe dynamic stochastic systems. It is a recursive algorithm where the state vector is updated as new information (Gibbs, 2011;Traslosheros et al, 2011;Simon, 2006). The uncertainty on the state vector's estimation decreases as the number of observations increases.…”

Section: Kalman Filtermentioning

confidence: 99%

Image-based control of delta parallel robots via enhanced LCM-CSM to track moving objects

Lopez-Lara

Maya

González

et al. 2020

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Purpose The purpose of this paper is to present a new vision-based control method, which enables delta-type parallel robots to track and manipulate objects moving in arbitrary trajectories. This constitutes an enhanced variant of the linear camera model-camera space manipulation (LCM-CSM). Design/methodology/approach After obtaining the LCM-CSM view parameters, a moving target’s position and its velocity are estimated in camera space using Kalman filter. The robot is then commanded to reach the target. The proposed control strategy has been experimentally validated using a PARALLIX LKF-2040, an academic delta-type parallel platform and seven different target trajectories for which the positioning errors were recorded. Findings For objects that moved manually along a sawtooth, zigzag or increasing spiral trajectory with changing velocities, a maximum positioning error of 4.31 mm was found, whereas objects that moved on a conveyor belt at constant velocity ranging from 7 to 12 cm/s, average errors between 2.2-2.75 mm were obtained. For static objects, an average error of 1.48 mm was found. Without vision-based control, the experimental platform used has a static positioning accuracy of 3.17 mm. Practical implications The LCM-CSM method has a low computational cost and does not require calibration or computation of Jacobians. The new variant of LCM-CSM takes advantage of aforementioned characteristics and applies them to vision-based control of parallel robots interacting with moving objects. Originality/value A new variant of the LCM-CSM method, traditionally used only for static positioning of a robot’s end-effector, was applied to parallel robots enabling the manipulation of objects moving along unknown trajectories.

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Section: Kalman Filtermentioning

confidence: 99%

Image-based control of delta parallel robots via enhanced LCM-CSM to track moving objects

Lopez-Lara

Maya

González

et al. 2020

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Visual servoing control of 4-DOF palletizing robotic arm for vision based sorting robot system

Cong

2022

Int J Interact Des Manuf

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Visual Servoing and Kalman Filter Applied to Parallel Manipulator 3-RRR

Daraviña,

Valencia,

Holguin

et al. 2024

Electronics

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This study introduces a novel methodology integrating computer vision, visual servo control, and the Kalman Filter to precisely estimate object locations for a 3-RRR planar type parallel manipulator. Through kinematic analysis and the development of a vision system using color indicators, the research enhances the ability of the manipulator to track object trajectories, especially in cases of occlusion. Employing Eye-to-Hand visual servo control, the research further refines the visual orientation of the sensor for optimal end effector and object identification. The incorporation of the Kalman Filter as a robust estimator for occluded objects underscores the predictive accuracy of the system. Results demonstrate the effectiveness of the methodology in trajectory generation and object tracking, with potential implications for improving robotic manipulators in dynamic environments. This comprehensive approach not only advances the fields of kinematic control and visual servoing but also opens new avenues for future research in complex spatial manipulations.

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Visual servoing for the Robotenis system: A strategy for a 3 DOF parallel robot to hit a Ping-Pong ball

Cited by 3 publications

References 14 publications

Image-based control of delta parallel robots via enhanced LCM-CSM to track moving objects

Image-based control of delta parallel robots via enhanced LCM-CSM to track moving objects

Visual servoing control of 4-DOF palletizing robotic arm for vision based sorting robot system

Visual Servoing and Kalman Filter Applied to Parallel Manipulator 3-RRR

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