• 제어로봇시스템학회:학술대회논문집
• /
• 1998.10a
• /
• pp.386-390
• /
• 1998

A master-slave system is proposed as a teaching device for a dual arm robot. The slave robots are remotely controlled by two delta-type master arms. In order to help the operator to observe the target object from the desired position and desired direction, cameras are mounted on a specialized manipulator, Movements of two slave arms are coordinated with that of the cameras. Due to this coordinated movements, the operator needs not to care the geometrical relation between the cameras and the slave robots.

• Journal of Electrical Engineering and Technology
• /
• v.10 no.4
• /
• pp.1830-1835
• /
• 2015

In this paper, we propose an algorithm for the automatic registration of two rigid parts using multiple 3D sensor systems on a robot. Four sets of structured laser stripe system consisted of a camera and a visible laser stripe is used for the acquisition of 3D information. Detailed procedures including extrinsic calibration among four 3D sensor systems and hand/eye calibration of 3D sensing system on robot arm are presented. We find a best pose using search-based pose estimation algorithm where cost function is proposed by reflecting geometric constraints between sensor systems and target objects. A pose with minimum gap and height difference is found by greedy search. Experimental result using demo system shows the robustness and feasibility of the proposed algorithm.

• Journal of the Korean Society of Industry Convergence
• /
• v.26 no.4_1
• /
• pp.545-551
• /
• 2023

In this paper, a robot automation methodology for chemical drum assembly in semiconductor industries are presented. Robot automation is essential to resolve safety issues in which operators are directly or indirectly exposed to chemicals or fumes in assembling dispense heads on chemical drums. However, the chemical drum assembling process involves complex and difficult tasks, such as mating male/female keycodes and fastening screws with large-diameter, which may be very difficult to be performed by a single-arm robot with a commercial rigid F/T sensor. In order to solve the problems, a method for assembling a chemical drum using dual-arm collaborative robot system, compliance F/T sensor, robot vision and gripper is presented.

• 제어로봇시스템학회:학술대회논문집
• /
• 1992.10b
• /
• pp.382-387
• /
• 1992

In order to obtain desired arc welding performance, we already developed an arc welding robot system that enabled coordinated motions of dual arm robots. In this system one robot arm holds a welding target as a positioning device, and the other robot moves the welding torch. Concerning to such a dual arm robot system, the positioning accuracy of robots is one important problem, since nowadays conventional industrial robots unfortunately don't have enough absolute accuracy in position. In order to cope with this problem, our robot system employed teaching playback method, where absolute error are compensated by the operator's visual feedback. Due to this system, an ideal arc welding considering the posture of the welding target and the directions of the gravity has become possible. Another problem still remains, while we developed an original teaching method of the dual arm robots with coordinated motions. The problem is that manual teaching tasks are still tedious since they need fine movements with intensive attentions. Therefore, we developed a 3-dimensional vision guided robot control method for our welding robot system with coordinated motions. In this paper we show our 3-dimensional vision sensor to guide our arc welding robot system with coordinated motions. A sensing device is compactly designed and is mounted on the tip of the arc welding robot. The sensor detects the 3-dimensional shape of groove on the target work which needs to be weld. And the welding robot is controlled to trace the grooves with accuracy. The principle of the 3-dimensional measurement is depend on the slit-ray projection method. In order to realize a slit-ray projection method, two laser slit-ray projectors and one CCD TV camera are compactly mounted. Tactful image processing enabled 3-dimensional data processing without suffering from disturbance lights. The 3-dimensional information of the target groove is combined with the rough teaching data they are given by the operator in advance. Therefore, the teaching tasks are simplified

• Proceedings of the IEEK Conference
• /
• 1999.06a
• /
• pp.496-499
• /
• 1999

This paper describes a medular neural network(MNN) for a vision system which tracks a given object using a sequence of images from a camera unit. The MNN is used to precisely recognize the given robot endeffector and to minize the processing time. Since the robot endeffector can be viewed in many different shapes in 3-D space, a MNN structure, which contains a set of feedforwared neural networks, co be more attractive in recognizing the given object. Each single neural network learns the endeffector with a cluster of training patterns. The training patterns for a neural network share the similar charateristics so that they can be easily trained. The trained MNN is less sensitive to noise and it shows the better performance in recognizing the endeffector. The recognition rate of MNN is enhanced by 14% over the single neural network. A vision system with the MNN can precisely recognize the endeffector and place it at the center of a display for a remote operator.

• Proceedings of the KIEE Conference
• /
• 1995.11a
• /
• pp.587-589
• /
• 1995

The safe navigation of a mobile robot requires the recognition of the environment in terms of vision processing. To be guided in the given path, the robot should acquire the information about where the wall and corridor are located. Also unexpected obstacles should be detected as rapid as possible for the safe obstacle avoidance. In the paper, we assume that the mobile robot should be navigated in the flat surface. In terms of this assumption we simplify the correspondence problem by the free navigation surface and matching features in that coordinate system. Basically, the vision processing system adopts line segment of edge as the feature. The extracted line segments of edge out of both image are matched in the free nevigation surface. According to the matching result, each line segment is labeled by the attributes regarding obstacle and free surface and the 3D shape of obstacle is interpreted. This proposed vision processing method is verified in terms of various simulations and experimentation using real images.

• 제어로봇시스템학회:학술대회논문집
• /
• 2003.10a
• /
• pp.767-771
• /
• 2003

In this study, stereo vision system is applied to a mobile manipulator for effective tasks. The robot can recognize a target and compute the position of the target using a stereo vision system. While a monocular vision system needs properties such as geometric shape of a target, a stereo vision system enables the robot to find the position of a target without additional information. Many algorithms have been studied and developed for an object recognition. However, most of these approaches have a disadvantage of the complexity of computations and they are inadequate for real-time visual servoing. However, color information is useful for simple recognition in real-time visual servoing. In this paper, we refer to about object recognition using colors, stereo matching method, recovery of 3D space and the visual servoing.

• Journal of Institute of Control, Robotics and Systems
• /
• v.11 no.5
• /
• pp.411-417
• /
• 2005

In this study, stereo vision system is applied to a mobile manipulator for effective tasks. The robot can recognize a target and compute the potion of the target using a stereo vision system. While a monocular vision system needs properties such as geometric shape of a target, a stereo vision system enables the robot to find the position of a target without additional information. Many algorithms have been studied and developed for an object recognition. However, most of these approaches have a disadvantage of the complexity of computations and they are inadequate for real-time visual servoing. Color information is useful for simple recognition in real-time visual servoing. This paper addresses object recognition using colors, stereo matching method to reduce its calculation time, recovery of 3D space and the visual servoing.

• Journal of KIISE:Software and Applications
• /
• v.37 no.8
• /
• pp.641-646
• /
• 2010

This paper presents algorithms for real-time navigation of a humanoid robot with a stereo vision but no other sensors. Using the algorithms, a robot can recognize its 3D environment by retrieving SIFT features from images, estimate its position through the Kalman filter, and plan its path to reach a destination avoiding obstacles. Our approach focuses on estimating the robot’s central walking path trajectory rather than its actual walking motion by using an approximate model. This strategy makes it possible to apply mobile robot localization approaches to humanoid robot localization. Simple collision free path planning and motion control enable the autonomous robot navigation. Experimental results demonstrate the feasibility of our approach.

• 제어로봇시스템학회:학술대회논문집
• /
• 2001.10a
• /
• pp.128.6-128
• /
• 2001

In this paper, we present a methodology of sensing and control for a robot system designed to be capable of grasping an object and moving it to target point Stereo vision system is employed to determine to depth map which represents the distance from the camera. In stereo vision system we have used a center-referenced projection to represent the discrete match space for stereo correspondence. This center-referenced disparity space contains new occlusion points in addition to the match points which we exploit to create a concise representation of correspondence an occlusion. And from the depth map we find the target object´s pose and position in 3-D space. To find the target object´s pose and position, we use the method of the model-based recognition.