• The Journal of Korea Robotics Society
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• v.19 no.1
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• pp.16-22
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• 2024

Robotic grasping in unstructured environments poses a significant challenge, demanding precise estimation of gripping positions for diverse and unknown objects. Generative Grasping Convolution Neural Network (GG-CNN) can estimate the position and direction that can be gripped by a robot gripper for an unknown object based on a three-dimensional depth map. Since GG-CNN uses only a depth map as an input, the precision of the depth map is the most critical factor affecting the result. To address the challenge of depth map precision, we integrate the Segment Anything Model renowned for its robust zero-shot performance across various segmentation tasks. We adjust the components corresponding to the segmented areas in the depth map aligned through external calibration. The proposed method was validated on the Cornell dataset and SurgicalKit dataset. Quantitative analysis compared to existing methods showed a 49.8% improvement with the dataset including surgical instruments. The results highlight the practical importance of our approach, especially in scenarios involving thin and metallic objects.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.507-514
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• 2022

Mobile manipulators are getting lime light in the field of home automation due to their mobility and manipulation capabilities. In this paper, we developed a small size manipulator system that can be mounted on a mobile robot as a preliminary study to develop a mobile manipulator. The developed manipulator has four degree-of-freedom. At the end-effector of manipulator, there are a camera and a gripper to recognize and manipulate the object. One of four degree-of-freedom is linear motion in vertical direction for better interaction with human hands which are located higher than the mobile manipulator. The developed manipulator was designed to dispose the four actuators close to the base of the manipulator to reduce rotational inertia of the manipulator, which improves stability of manipulation and reduces the risk of rollover. The developed manipulator repeatedly performed a pick and place task and successfully manipulate the object within the workspace of manipulator.

• Journal of Bio-Environment Control
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• v.28 no.4
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• pp.322-327
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• 2019

This study was conducted to improve the performance of automatic grafting robot using image recognition technique. The stem diameters of tomatoes and cucumber at the time of grafting were $2.5{\pm}0.3mm$ and $2.2{\pm}0.2mm$ for scions and $3.1{\pm}0.7mm$ and $3.6{\pm}0.3mm$ for rootstocks, respectively. The grafting failure was occurred when the different height between scions and rootstocks were over 4 mm and below 2 mm due to the small contact area of both cutting surface. Therefore, it was found that the height difference at the cutting surface of 3 mm is appropriate. This study also found that grafting failure was occurred when the stem diameters of both scions and rootstocks were thin. Therefore, it was suggested to use at least one stem with thicker than the average stem diameter. Field survey on the cutting angle of stems by hand were ranged from 13 to 55 degree for scions and 15 to 67 degree for rootstocks, respectively, which indicates that this could cause the grafting failure problem. However, the automatic grafting robot developed in this study rotates the seedlings 90 degree and then the stems are cut using a cutting blade. The control part of robot use all images taken from grafting process to determine the distance between a center of both ends of stem and a gripper center and then control the rotation angle of a gripper. Overall, this study found that The performance of automatic grafting robot using image recognition technique was superior with the grafting success rates of cucumber and tomato as $96{\pm}3.2%$ and $95{\pm}4%$, respectively.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.12
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• pp.1160-1166
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• 2013

This paper presents feedforward controllers to improve the control performance of the motion and grasping force of a surgical instrument used in an MIS (Minimally Invasive Surgery) robot. The surgical instrument has a long distance between the drive motors and its active joints. Therefore, the gripper on the instrument is controlled by a cable drive mechanism, which generates a coupled motion between the wrist joint and the grip direction. In order to solve the problem, this paper analyzes the pulley composition of the surgical instrument and proposes feedforward controllers to eliminate the coupled motion. Furthermore, feedforward controllers to regulate the grasping force are proposed to deal with another coupling problem between the grasping force of the instrument and the motion of the instrument joints. The experimental results demonstrate the improved control performance of the motion and grasping force of the instrument.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.53 no.2
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• pp.127-134
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• 2004

In this paper, human motor behaving model based sensory motor coordination(SMC) algorithm is implemented on robotic grasping task. Compare to conventional SMC models which connect sensor to motor directly, the proposed method used biologically inspired human behaving system in conjunction with SMC algorithm for fast grasping force control of robot arm. To characterize various grasping objects, pressure sensors on hand gripper were used. Measured sensory data are simultaneously transferred to perceptual mechanism(PM) and long term memory(LTM), and then the sensory information is forwarded to the fastest channel among several information-processing flows in human motor system. In this model, two motor learning routes are proposed. One of the route uses PM and the other uses short term memory(STM) and LTM structure. Through motor learning procedure, successful information is transferred from STM to LTM. Also, LTM data are used for next moor plan as reference information. STM is designed to single layered perception neural network to generate fast motor plan and receive required data which comes from LTM. Experimental results showed that proposed method can control of the grasping force adaptable to various shapes and types of greasing objects, and also it showed quicker grasping-behavior lumining time compare to simple feedback system.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.19 no.10
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• pp.111-116
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• 2020

Flexible tactile sensors, which are primarily used as grippers in robots, are mainly used to handle highly elastic or highly flexible objects. That is, flexible grippers are used when an object cannot be sufficiently controlled by applying a specific output force or taking a specific grabbing action. This is because a flexible tactile sensor needs to measure the pressure applied directly to held objects while deforming according to the shape of the object to be handled. CNT-based sensors used to be made from a highly flexible polymer to give flexibility and it is known that the sensors are greatly affected by the contact resistance of the terminal that connects the sensor to an electrical circuit; therefore, this paper clarifies the contact resistance of MWCNTs-based flexible tactile sensors and terminals. The effects of main and plating materials for terminals are investigated and the combinations of main and plating materials that exhibit contact resistance are measured in a typical industrial environment.

• Journal of Bio-Environment Control
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• v.23 no.2
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• pp.123-130
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• 2014

Oriental melon (Cucumis melo var. makuwa) should be cultivated on the soil and be harvested. It is difficult to find because it is covered with leaves, and furthermore, it is very hard to grip it due to its climbing stems. This study developed and tested oriental melon harvesting robots such as an end-effector, manipulator and identification device. The end effector is divided into a gripper for harvest and a cutter for stems. In addition, it was designed to control the gripping and cutting forces so that the gripper could move four fingers at the same time and the cutter could move back and forth. The manipulator was designed to realize a 4-axis manipulator structure to combine orthogonal coordinate-type and shuttle-type manipulators with L-R type model to rotate based on the central axis. With regard to the identification device, oriental melon was identified using the primary identification global view camera device and secondary identification local view camera device and selected in the prediction of the sugar content or maturity. As a result of the performance test using this device, the average harvest time was 18.2 sec/ea, average pick-up rate was 91.4%, average damage rate was 8.2% and average sorting rate was 72.6%.

• Journal of Bio-Environment Control
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• v.22 no.3
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• pp.284-290
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• 2013

This study analyzed the geometric, compressive, cutting and friction properties of oriental melons in order to design a gripper capable of soft handling and a cutter for cutting oriental melon vine among the end effector of oriental melon as a preliminary step for developing the end effector of the robot capable of harvesting oriental melons in protected cultivation. As a result, the average length, diameter at the midpoint, weight, volume and roundness of the oriental melons were 108 mm, 70 mm, 188 g, 333 mL and 3.8 mm. Nonlinear regression analysis was performed on the equation $W=L^a{\times}D_2^b$ with variation of the length (L) and diameter (D2) of the weight (W) of the oriental melons. As a result, it was shown that there was a correlation between a of 2.0279 and b of -0.9998 as a constant value. The average diameter of the oriental melon vine was 3.8 mm, and most vines were distributed within a radius of 5 mm from the center. The average yield value, compressive strength and hardness of the oriental melons were $36.5N/cm^2$, $185.7N/cm^2$ and $636.7N/cm^2$, respectively. The average cutting force and shear strength of the oriental melon vines were $2.87{\times}10^{-2}\;N$ and $5.60N/cm^2$, respectively. The maximum friction coefficient of the oriental melons was rubber of 0.609, followed by aluminium of 0.393, stainless steel of 0.177 and teflon of 0.079. It was considered possible to apply it to the size of the gripper and cutter, turning radius, dynamics of drive motor and selection of materials and their quality in light of the position error and safety factor according to the movement when designing end effector based on the analyzed data.