Computer vision-based high-quality tea automatic plucking robot using Delta parallel manipulator

Yang, Hualin; Chen, Long; Ma, Zongwen; Chen, Miaoting; Zhong, Yan; Deng, Fang; Li, Maozhen

doi:10.1016/j.compag.2020.105946

Cited by 70 publications

(32 citation statements)

References 28 publications

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“…The implemented algorithm calculates the size Area of the objects and identifies which object is bigger than the other then the robot will pick up according to the big in size and on the other hand, the algorithm is based on blue color for the target then the robot will select according to the color. In this case, the blue color was set as the detection target [11]. Human hand was used as a simulating motion of the delta robot as a moving platform.…”

Section: Implementation and Resultmentioning

confidence: 99%

“…The design objectives of this robot involve high reliability and stability, accurate recognition, localization of objects, high efficient pick and place manipulation, ease maintenance and cost effectiveness. Hence, the computer vision technique is executed to recognize and select objects based on size or color and accurately localize picking point and placing (dropping) point based on using visual recognition system which has a camera combined with corresponding algorithms [11]. The end effector has 3 DOF which permit the robot to have enough flexibility to rotate in any direction and is going to handle materials smoothly.…”

Section: Introductionmentioning

confidence: 99%

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Modelling and Simulation of a 3DOF End Effector for Material Handling with a Delta Robot

Musa

2022

J. Phys.: Conf. Ser.

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In order to improve workspace and material handling system of the delta robot, This paper describes a design of an End-effector with 3 degrees of freedom (3DOF) which makes the End-effector more flexible and having sufficient range of working space. This End-effector will be mounted on a delta parallel robot to perform the desired task in handling materials accordingly. The robot is able to pick and place a given material to the right place and positioning as it is desired by the user. The methodology used to design this robot was based on 3 major components which are: Sliding rails which deals with translational motion along horizontal axis, this motion carries the whole system from side to side and is going to play a role of increasing workspace in either assembling line or picking and placing system. Delta robot is in charge of manipulating its end effector in 3 dimensions along (x, y, z - axis) according to the object tracking localization as a human’s arm manipulate the hand. The end effector’s purpose is to perform rotational motion then pick the object and place as the system requires, this performance has advantage of handling materials and positioning respectively. It showed that the proposed system is safe and is feasible for application. The proposed material handling system can minimize the disadvantages of utilizing a delta robot by attachment of the presented end-effector to the delta robot.

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Section: Implementation and Resultmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modelling and Simulation of a 3DOF End Effector for Material Handling with a Delta Robot

Musa

2022

J. Phys.: Conf. Ser.

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“…Du et al [8] proposed a binocular vision-based object recognition and robotic grasping strategy. Yang et al [9] built a vision recognition system (VRS) based on the YOLOv3 model to improve the efficiency of picking robots. Matsuo et al [10] investigated the robots in logistics handling in warehouses and convenience stores, where multi-object grasping was achieved through the dual-arm operation.…”

Section: Introductionmentioning

confidence: 99%

A New Kinect V2-Based Method for Visual Recognition and Grasping of a Yarn-Bobbin-Handling Robot

et al. 2022

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This work proposes a Kinect V2-based visual method to solve the human dependence on the yarn bobbin robot in the grabbing operation. In this new method, a Kinect V2 camera is used to produce three-dimensional (3D) yarn-bobbin point cloud data for the robot in a work scenario. After removing the noise point cloud through a proper filtering process, the M-estimator sample consensus (MSAC) algorithm is employed to find the fitting plane of the 3D cloud data; then, the principal component analysis (PCA) is adopted to roughly register the template point cloud and the yarn-bobbin point cloud to define the initial position of the yarn bobbin. Lastly, the iterative closest point (ICP) algorithm is used to achieve precise registration of the 3D cloud data to determine the precise pose of the yarn bobbin. To evaluate the performance of the proposed method, an experimental platform is developed to validate the grabbing operation of the yarn bobbin robot in different scenarios. The analysis results show that the average working time of the robot system is within 10s, and the grasping success rate is above 80%, which meets the industrial production requirements.

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“…Yanfang Yuan et al addressed the problem of easy collision between two manipulators in the process of tea picking, partitioned the picking area and then constrained the manipulator movement path to "M" type, which has a better planning effect [15]. For tea picking, Hualin Yang designed a movement track of the manipulator shaped like ∩ to avoid obstacles and damage to other branches [16].…”

Section: Introductionmentioning

confidence: 99%

Picking Path Planning Method of Dual Rollers Type Safflower Picking Robot Based on Improved Ant Colony Algorithm

Zhang

Sun

et al. 2022

Processes

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Aiming at the problem of automatic path planning for the whole safflower bulbs during the operation of safflower picking robots, an improved ant colony algorithm (ACA) was proposed to plan the three-dimensional path of the safflower picking points. The shortest time and distance were taken as the overall goal of path planning to comprehensively improve the working efficiency of safflower picking robots. First, in order to shorten time, the angle induction factor was introduced to reduce the angle rotation of the end-effector. Second, in order to shorten the length of the picking path, the picking track was optimized. Finally, the design of the secondary path optimization reduced the number of picking points, which not only shortened the length of the picking path, but also shortened the picking time. The simulation results show that the path planned by the improved ACA was reduced by three picking points, shortening the total length by 74.32%, and reducing the picking time by 0.957 s. The simulation results verify the feasibility of the improved ACA for safflower picking path planning, which provides theoretical reference and technical support for the picking path planning of dual roller safflower picking robots.

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Computer vision-based high-quality tea automatic plucking robot using Delta parallel manipulator

Cited by 70 publications

References 28 publications

Modelling and Simulation of a 3DOF End Effector for Material Handling with a Delta Robot

Modelling and Simulation of a 3DOF End Effector for Material Handling with a Delta Robot

A New Kinect V2-Based Method for Visual Recognition and Grasping of a Yarn-Bobbin-Handling Robot

Picking Path Planning Method of Dual Rollers Type Safflower Picking Robot Based on Improved Ant Colony Algorithm

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