Coordinate-based control for a materials handling equipment utilizing real-time simulation

Roozbahani, Hamid; Alizadeh, Marjan; Ahomäki, Antti; Handroos, Heikki

doi:10.1016/j.autcon.2020.103483

Cited by 5 publications

(1 citation statement)

References 18 publications

(19 reference statements)

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“…Model predictive control (MPC) is a strategy to achieve control effects through repeated optimization and feedback correction of the predictive model, which has good robustness and control effects [28,29] . Therefore, the predictive control method of the manipulator model is proposed, which regards the dynamic feature points of the assembly line lettuce as the solution and ensures the real-time dynamic tracking of the manipulator.…”

Section: Model Building and Mpc Controller Designmentioning

confidence: 99%

Intelligent sorting method for assembly line based on visual positioning and model predictive control of robotic arm

Zhang,

Lu,

Jian

et al. 2023

International Journal of Agricultural and Biological Engineering

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The existing steering device in the fruit and vegetable packaging assembly line cannot adjust the attitude of lettuce to a unified attitude, affecting the input and packaging process of the packaging machine. This study proposes an intelligent assembly line sorting method based on the visual positioning and model predictive control of a robotic arm. First, lightweight improvement based on the YOLOv5 is realized, the lettuce stalk in the background of the conveyor belt is promptly identified, the image of the lettuce stalk in the anchor box area is processed, and the edge contour point set is determined to extract the pixel coordinates of the optimal grasp point and mirror inclination angle of the lettuce. For the intelligent assembly line system, a robot arm kinematics model is constructed and the robot kinematics inverse solutions are calculated. Additionally, the lettuce movement speeds are dynamically measured by the vision system. A combination of the model prediction control, dynamic tracking, and rapid sorting of the lettuce by the robot claw is realized. The results show that the average detection time of a single frame image in the visual positioning part is 0.014 s, which is reduced by 50%; the accuracy and recall are 98% and 95%, respectively. The detection time is significantly reduced by ensuring accuracy. Within the current speed range of the packaging assembly line conveyor belt, the manipulator can grasp lettuce at different speeds stably and fast; the average axial error, average radial error, and adjusted average inclination angle error are 0.71 cm, 1.02 cm, and 3.79°, respectively, verifying the high efficiency and stability of the model. The proposed method of this study enables application in the intelligent sorting operation of industrial assembly lines

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Section: Model Building and Mpc Controller Designmentioning

confidence: 99%