• Journal of Institute of Control, Robotics and Systems
• /
• v.16 no.7
• /
• pp.674-680
• /
• 2010

It is known that many insects and animals can return to their nest after exploration, with their own specific homing mechanisms. Their homing navigation methods have been applied to the robotic navigation. In this paper, we test the sector-based image matching method motivated by the honeybee's landmark navigation behaviour. Here, our robotic approach uses the reference compass to identify the current head direction and the relative angular position of landmarks for the navigation. The robot shows desirable homing behaviors if the robot is surrounded by landmarks. The result of robot experiment is in good agreement with that of simulation.

• Journal of Technologic Dentistry
• /
• v.12 no.1
• /
• pp.95-102
• /
• 1990

The distances from the center line between maxillary right and left central incisors(the dental midline) to the various anatomical landmarks were measured. Fifty five students(thirth four males and twenty one females) who have at least natural teeth including maxillary and mandibular incisors and bicuspids were examined. 1. There was statistically significant difference between the dental midline and the center line of maxillary labial frenum(p<0.05). 2. There was no statistically significant difference between the dental midline and the point of incisive papilla, philtrum line, the center line between two mandibular central incisors, and the median palatine suture line(p>0.05). 3. There was no statistically significant sexual difference among data. 4. The philtrum line showed the highest value of correspondence to the center line between two maxillary central incisors followed by the center point of incisive papilla, the center line of two mandibular central incisors, median plaltine suture line and the center line of maxillary labial frenum at the decreasing rate.

• Proceedings of the KIEE Conference
• /
• 1999.07g
• /
• pp.3048-3050
• /
• 1999

This paper suggests a position estimating algorithm using mono vision system with projective geometry method. Generally, 3-D information can not be easily extracted from mono vision system which is taken by a camera at a specific point. But this defect is overcome by adopting model-based image analysis and selecting lines and points on the ground as natural landmarks. And this paper suggests a method that estimates position from many natural landmarks by distance error weight function.

• The Journal of Korea Robotics Society
• /
• v.10 no.2
• /
• pp.112-118
• /
• 2015

This paper proposes a pose-graph based SLAM method using an upward-looking camera and artificial landmarks for AGVs in factory environments. The proposed method provides a way to acquire the camera extrinsic matrix and improves the accuracy of feature observation using a low-cost camera. SLAM is conducted by optimizing AGV's explored path using the artificial landmarks installed on the ceiling at various locations. As the AGV explores, the pose nodes are added based on the certain distance from odometry and the landmark nodes are registered when AGV recognizes the fiducial marks. As a result of the proposed scheme, a graph network is created and optimized through a G2O optimization tool so that the accumulated error due to the slip is minimized. The experiment shows that the proposed method is robust for SLAM in real factory environments.

• The Journal of Korea Robotics Society
• /
• v.14 no.1
• /
• pp.14-21
• /
• 2019

In the ground environment, mobile robot research uses sensors such as GPS and optical cameras to localize surrounding landmarks and to estimate the position of the robot. However, an underwater environment restricts the use of sensors such as optical cameras and GPS. Also, unlike the ground environment, it is difficult to make a continuous observation of landmarks for location estimation. So, in underwater research, artificial markers are installed to generate a strong and lasting landmark. When artificial markers are acquired with an underwater sonar sensor, different types of noise are caused in the underwater sonar image. This noise is one of the factors that reduces object detection performance. This paper aims to improve object detection performance through distortion and rotation augmentation of training data. Object detection is detected using a Faster R-CNN.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2012.05a
• /
• pp.323-324
• /
• 2012

• 제어로봇시스템학회:학술대회논문집
• /
• 2002.10a
• /
• pp.34.2-34
• /
• 2002

● Introduction ● The environment of the RoboSot ● Extracting landmarks & feature points ● Experimental results ● Conclusion

• Clinics in Shoulder and Elbow
• /
• v.21 no.3
• /
• pp.111-112
• /
• 2018

• Maxillofacial Plastic and Reconstructive Surgery
• /
• v.28 no.3
• /
• pp.222-228
• /
• 2006

Various methods have been used in the past to indirectly analyze the craniofacial region. Among these, the lateral and posterior-anterior cephalometircs are used for the evaluation of the dentofacial deformities. However, cephalometircs create inaccuracies because of the inherent enlargement and distortion of the image. The interpretation of cephalometric films is also problematic: the number of anatomic landmarks that can be identified accurately is limited, and the overlap of structures on a radiograph making locating these landmarks difficult. To overcome these problems, computed tomography(CT) has been recommended as an useful modality in the diagnosis, surgical planning, and follow-up of craniofacial anomalies. There is no significant enlargement or distortion of the image, overlap of structure, or tracing error. And the number of anatomic landmarks is vast. The purpose of this study was to examine the orbit and midfacial region using Occlusal Maxillary CT, consisted of slices parallel to the occlusal plane. Based on these CT scan, we provide the data that could be applied to monitor an individual patient's skeletal pattern and the guide to the maxillary osteotomy.

• Journal of the Korea Society of Computer and Information
• /
• v.25 no.1
• /
• pp.63-69
• /
• 2020

In this paper, we propose an indoor positioning technique using the landmark based on relative Access Point (AP) signal strengths. The absolute values of AP signals are used to conventional indoor positioning technologies, but they may be different because of the difference of the measuring device, the measuring environment, and the timing of the measurements. However, we found the fact that the flow of the AP's RSSI in certain places shows almost constant patterns. Based on theses characteristics, we identify the relative strength between the APs and store the certain places as landmarks where they show certain patterns. Once the deployment of the landmark map is complete, system calculate position of user using the IMU sensor of smartphone and calibrate it with stored landmarks. Our system shows 75.2% improvement over technology that used only sensors, and 39.6% improvement over technology that used landmarks that were selected with absolute values.