• Proceedings of the Korean Institute Of Construction Engineering and Management
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• autumn
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• pp.173-179
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• 2003

Techniques to rapidly model local spaces, using 3D range data can enable implementation of: (1) real-time obstacle avoidance for improved safety, (2) advanced automated equipment control modes, and (3) as-built data acquisition for improved quantity tracking, engineering, and project control systems. The objective of the research reported here was to introduce current rapid local modeling techniques and develop rapid local spatial modeling tools.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.339-339
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• 2000

In this parer, a method of measuring the size of defects on the wall and restructing the defect image of 3-dimension is developed based on the tracking algorithm of a camera position which uses the inclination angle of line slit beam for overcoming the difficulty of the corresponding problem identifying the image point in the both image. In the experiments, an algorithm for estimating the horizontal angle of CCD camera is presented and validated by applying it to the measurement of area and length under the variations of both the distance and the angle of CCD camera. And its performance is compared to that of the rotating and mapping method of image which has the Euclidian distance.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1077-1081
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• 2003

In this paper, experimental studies of force tracking control for the crack sealing robot are presented. Crack sealing robot is built to detect, track and seal the crack on the pavement. Before sealing, crack must be detected by a laser sensor and a camera sensor, then cleaned for a better sealing job. In order to maintain contact with the ground force control is required to brush all dirt in the crack out for preparing sealing cracks with tars. Impedance control algorithm is presented to regulate a specified desired force. Experimental studies of the proposed force control algorithm are conducted under unknown environment stiffness and location. Performances of force control algorithm are stable and excellent.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.2
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• pp.218-222
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• 2014

In this paper, we introduce an autonomous calibration method for a 2D laser displacement sensor (e.g. laser vision sensor and laser range finder) by matching a single point on a flat structure. Many arc welding robots install a 2D laser displacement sensor to expand their application by recognizing their environment (e.g. base metal and seam). In such systems, sensing data should be transformed to the robot's coordinates, and the geometric relation (i.e. rotation and translation) between the robot's coordinates and sensor coordinates should be known for the transformation. Calibration means the inference process of geometric relation between the sensor and robot. Generally, the matching of more than 3 points is required to infer the geometric relation. However, we introduce a novel method to calibrate using only 1 point matching and use a specific flat structure (i.e. circular hole) which enables us to find the geometric relation with a single point matching. We make the rotation component of the calibration results as a constant to use only a single point by moving a robot to a specific pose. The flat structure can be installed easily in a manufacturing site, because the structure does not have a volume (i.e. almost 2D structure). The calibration process is fully autonomous and does not need any manual operation. A robot which installed the sensor moves to the specific pose by sensing features of the circular hole such as length of chord and center position of the chord. We show the precision of the proposed method by performing repetitive experiments in various situations. Furthermore, we applied the result of the proposed method to sensor based seam tracking with a robot, and report the difference of the robot's TCP (Tool Center Point) trajectory. This experiment shows that the proposed method ensures precision.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.513-520
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• 2011

This paper presents the motion planning of robotic vehicles for the path tracking and the obstacle avoidance. To follow the given path, the vehicle moves through the turning radius obtained through the pure pursuit method, which is a geometric path tracking method. In this paper, we assume that the vehicle is equipped with a 2D laser scanner, allowing it to avoid obstacles within its sensing range. The turning radius for avoiding the obstacle, which is inversely proportional to the virtual force, is then calculated. Therefore, these two kinds of the turning radius are used to generate the steering angle for the front wheel of the vehicle. And the vehicle reduces the velocity when it meets the obstacle or the large steering angle using the potentials of obstacle points and the steering angle. Thus the motion planning of the vehicle is done by planning the steering angle for the front wheels and the velocity. Finally, the performance of the proposed method is tested through simulation.

• Journal of Institute of Control, Robotics and Systems
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• v.8 no.9
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• pp.776-787
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• 2002

Automation of welding process in shipyards is ultimately necessary, since the welding site is spatially enclosed by floors and girders, and therefore welding operators are exposed to hostile working conditions. To solve this problem, a welding mobile robot that can navigate autonomously within the enclosure has been developed. To achieve the welding task in the closed space, the robotic welding system needs a sensor system for the working environment recognition and the weld seam tracking, and a specially designed environment recognition strategy. In this paper, a three-dimensional laser vision system is developed based on the optical triangulation technology in order to provide robots with 3D work environmental map. Using this sensor system, a spatial filter based on neural network technology is designed for extracting the center of laser stripe, and evaluated in various situations. An environment modeling algorithm structure is proposed and tested, which is composed of the laser scanning module for 3D voxel modeling and the plane reconstruction module for mobile robot localization. Finally, an environmental recognition strategy for welding mobile robot is developed in order to recognize the work environments efficiently. The design of the sensor system, the algorithm for sensing the partially structured environment with plane segments, and the recognition strategy and tactics for sensing the work environment are described and discussed with a series of experiments in detail.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.5
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• pp.453-464
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• 2012

This is a research of an adaptive longitudinal control system for situated cognition in wide range, traffic accidents reduction and safety driving environment by integrated system which graft a road infrastructure's information based on IT onto the intelligent vehicle combined automobile and IT technology. The road infrastructure installed by laser scanner in intersection, speed limited area and sharp curve area where is many risk of traffic accident. The road infra conducts objects recognition, segmentation, and tracking for determining dangerous situation and communicates real-time information by Ethernet with vehicle. Also, the data which transmitted from infrastructure supports safety driving by integrated with laser scanner's data on vehicle bumper.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.10
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• pp.1051-1056
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• 2014

In this paper, we introduce an intelligent robotic arc welding system which exploits sensors like as LVS (Laser Vision Sensor), Hall effect sensor, voltmeter and so on. The use of industrial robot is saturated because of its own limitation, and one of the major limitations is that industrial robot cannot recognize the environment. Lately, sensor-based environmental awareness research of the industrial robot is performed actively to overcome such limitation, and it can expand application field and improve productivity. We classify the sensor-based intelligent arc welding robot system by the goal and the sensing data. The goals can be categorized into detection of a welding start point, tracking of a welding line and correction of a torch deformation. The Sensing data can be categorized into welding data (i.e. current, voltage and short circuit detection) and displacement data (i.e. distance, position). This paper covers not only the explanation of the each category but also its advantage and limitation.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1137-1140
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• 2005

Automatic welding has been used frequently on pipeline projects. The productivity and reliability are most essential features of the automatic welding system. The mechanized GMAW process is the most widely used welding process and the carriage and band system is most effective welding system for pipeline laying. This application-oriented paper introduces new automatic welding equipment for pipeline construction. It is based on cutting-edge design and practical welding physics to minimize downtime. This paper also describes the control system which was designed and implemented for new automatic welding equipment. The system has the self diagnostic function which facilitates maintenance and repairs, and also has the network function via which the welding task data can be transmitted and the welding process data can be monitored. The laser vision sensor was designed for narrow welding groove in order to implement higher accuracy of seam tracking and fully automatic operation.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.14 no.1
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• pp.131-147
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• 2020

RFID (Radio Frequency Identification) identifies a specific object by radio signals. As the tag provides a unique ID for the purpose of identification, RFID technology effectively solves the ambiguity and occlusion problem that challenges the laser or camera-based approach. This paper proposes an approach to track a moving object based on the integration of RFID and laser ranging information using a particle filter. To be precise, we split laser scan points into different clusters which contain the potential moving objects and calculate the radial velocity of each cluster. The velocity information is compared with the radial velocity estimated from RFID phase difference. In order to achieve the positioning of the moving object, we select a number of K best matching clusters to update the weights of the particle filter. To further improve the positioning accuracy, we incorporate RFID signal strength information into the particle filter using a pre-trained sensor model. The proposed approach is tested on a SCITOS service robot under different types of tags and various human velocities. The results show that fusion of signal strength and laser ranging information has significantly increased the positioning accuracy when compared to radial velocity matching-based or signal strength-based approaches. The proposed approach provides a solution for human machine interaction and object tracking, which has potential applications in many fields for example supermarkets, libraries, shopping malls, and exhibitions.