• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2003년도 ICCAS
• /
• pp.639-644
• /
• 2003

An unstructured environment requires a robot to possess outstanding mobility and advanced control algorithms since there exist complicated configurations such as obstacle, uneven surface, etc. Especially, when a quadruped robot walks in these environments, obstacles in the walking route will obstruct the walking or may give rise to a serious trouble. In this paper, we introduce a strategy for the stable walking in unstructured environment. The proposed strategy consists of two control algorithms. One is a collision{free algorithm to avoid obstacles and the other is an algorithm to overcome any obstacle. These are based on the obstacle detection method and a shape reconstruction algorithm, Which algorithms are described in detail. In addition, the validity of these algorithms have been demonstrated through experiments using a quadruped walking robot called "MRWALLSPECT III(Multifunctional Robot for Wall inSPECTion version 3 )".

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 1998년도 하계학술대회 논문집 G
• /
• pp.2246-2248
• /
• 1998

To control the remote system in the unstructured environment requires data under certain circumstances. When a machine is dealt with an unstructured environment, new environment structure is to be composed. The stereo vision system can get both the intensity data and the range data. So, in this paper, data architecture of a stereo image is proposed to set them.

• 한국전자통신학회논문지
• /
• 제17권6호
• /
• pp.1243-1248
• /
• 2022

비정형 환경인 건설 현장에서 안정적으로 운영할 수 있는 이동 플랫폼은 스마트 건설기술 개발에 있어 중요한 문제이다. 본 논문에서는 건설 현장 지형정보 수집 지원을 위해 비정형 환경에서도 강인하게 주행할 수 있는 이동 로봇 플랫폼을 소개한다. 제안한 이동 플랫폼은 종경사 뿐만이 아닌 횡경사에도 대처할 수 있도록 설계하였으며 시뮬레이션 실험을 통해 제안한 플랫폼의 단차 극복성능을 분석하였다.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• 제9권8호
• /
• pp.3182-3202
• /
• 2015

Flexibly expanding the storage capacity required to process a large amount of rapidly increasing unstructured log data is difficult in a conventional computing environment. In addition, implementing a log processing system providing features that categorize and analyze unstructured log data is extremely difficult. To overcome such limitations, we propose and design a MongoDB-based unstructured log processing system (MdbULPS) for collecting, categorizing, and analyzing log data generated from banks. The proposed system includes a Hadoop-based analysis module for reliable parallel-distributed processing of massive log data. Furthermore, because the Hadoop distributed file system (HDFS) stores data by generating replicas of collected log data in block units, the proposed system offers automatic system recovery against system failures and data loss. Finally, by establishing a distributed database using the NoSQL-based MongoDB, the proposed system provides methods of effectively processing unstructured log data. To evaluate the proposed system, we conducted three different performance tests on a local test bed including twelve nodes: comparing our system with a MySQL-based approach, comparing it with an Hbase-based approach, and changing the chunk size option. From the experiments, we found that our system showed better performance in processing unstructured log data.

• 제어로봇시스템학회논문지
• /
• 제18권12호
• /
• pp.1115-1121
• /
• 2012

This paper proposes a method to extract accurate plane of an object in unstructured environment for a humanoid robot by using a laser scanner. By panning and tilting 2D laser scanner installed on the head of a humanoid robot, 3D depth map of unstructured environment is generated. After generating the 3D depth map around a robot, the proposed plane extraction method is applied to the 3D depth map. By using the hierarchical clustering method, points on the same plane are extracted from the point cloud in the 3D depth map. After segmenting the plane from the point cloud, dimensions of the planes are calculated. The accuracy of the extracted plane is evaluated with experimental results, which show the effectiveness of the proposed method to extract planes around a humanoid robot in unstructured environment.

• 로봇학회논문지
• /
• 제16권3호
• /
• pp.179-188
• /
• 2021

Construction monitoring is one of the key modules in smart construction. Unlike structured urban environment, construction site mapping is challenging due to the characteristics of an unstructured environment. For example, irregular feature points and matching prohibit creating a map for management. To tackle this issue, we propose a system for data acquisition in unstructured environment and a framework for Intensity and Ambient Enhanced Lidar Inertial Odometry via Smoothing and Mapping, IA-LIO-SAM, that achieves highly accurate robot trajectories and mapping. IA-LIO-SAM utilizes a factor graph same as Tightly-coupled Lidar Inertial Odometry via Smoothing and Mapping (LIO-SAM). Enhancing the existing LIO-SAM, IA-LIO-SAM leverages point's intensity and ambient value to remove unnecessary feature points. These additional values also perform as a new factor of the K-Nearest Neighbor algorithm (KNN), allowing accurate comparisons between stored points and scanned points. The performance was verified in three different environments and compared with LIO-SAM.

• 로봇학회논문지
• /
• 제8권4호
• /
• pp.247-255
• /
• 2013

This paper shows the development of a snake robot (KAEROT-snake V) which consists of 16 1-DOF actuator modules and head module. The modules are connected serially and the joint axis of each module is rotated by $90^{\circ}$ with respect to the previous joint so that the snake robot can move in the 3D space. A tail actuator module includes slip-ring and metal connector. KAEROT-snake IV developed in prior research could move in the 3D space and climb up in a narrow pipe. But its design was not appropriate to the unstructured tough environment and its speed was somewhat slow. A new actuator module is designed to enclose all parts of the module so that any wire is not exposed. The size and weight of the new module was slightly reduced. And the rotation speed and torque of the joint was increased by about twice when compared with pre-module. An embedded controller was developed so small that it can be mounted inside the module. The performance of the developed robot was demonstrated through various locomotion experiments.

• 한국융합학회논문지
• /
• 제12권7호
• /
• pp.45-51
• /
• 2021

급속한 비대면 환경과 모바일 우선 전략에 따라 해마다 많은 정형/비정형 데이터의 폭발적인 증가와 생성은 모든 분야에서 빅데이터를 활용한 새로운 의사 결정과 서비스를 요구하고 있다. 그러나 매년 급속히 증가하는 빅데이터를 활용하여 실무 환경에서 적용 가능한 표준 플랫폼으로 빅데이터를 수집하여 적재한 후, 정재한 빅데이터를 관계형 데이터베이스에 저장하고 처리하는 하둡 에코시스템 활용의 참조 사례들은 거의 없었다. 따라서 본 연구에서는 스프링 프레임워크 환경에서 3대의 가상 머신 서버를 통하여 하둡 2.0을 기반으로 쇼셜 네트워크 서비스에서 키워드로 검색한 비정형 데이터를 수집한 후, 수집된 비정형 데이터를 하둡 분산 파일 시스템과 HBase에 적재하고, 적재된 비정형 데이터를 기반으로 형태소 분석기를 이용하여 정형화된 빅데이터를 관계형 데이터베이스에 저장할 수 있게 설계하고 구현하였다. 향후에는 데이터 심화 분석을 위한 하이브나 머하웃을 이용하여 머신 러닝을 이용한 클러스터링과 분류 및 분석 작업 연구가 지속되어야 할 것이다.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• 제8권1호
• /
• pp.82-86
• /
• 2008

The article presents ARTMAP and Fuzzy BK-Product approach underwater obstacle avoidance for the Autonomous underwater Vehicles (AUV). The AUV moves an unstructured area of underwater and could be met with obstacles in its way. The AUVs are equipped with complex sensorial systems like camera, aquatic sonar system, and transducers. A Neural integrated Fuzzy BK-Product controller, which integrates Fuzzy logic representation of the human thinking procedure with the learning capabilities of neural-networks (ARTMAP), is developed for obstacle avoidance in the case of unstructured areas. In this paper, ARTMAP-Fuzzy BK-Product controller architecture comprises of two distinct elements, are 1) Fuzzy Logic Membership Function and 2) Feed-Forward ART component. Feed-Forward ART component is used to understanding the unstructured underwater environment and Fuzzy BK-Product interpolates the Fuzzy rule set and after the defuzzyfication, the output is used to take the decision for safety direction to go for avoiding the obstacle collision with the AUV. An on-line reinforcement learning method is introduced which adapts the performance of the fuzzy units continuously to any changes in the environment and make decision for the optimal path from source to destination.

• Environmental Sciences Bulletin of The Korean Environmental Sciences Society
• /
• 제10권S_1호
• /
• pp.23-28
• /
• 2001

A new numerical weather prediction and dispersion model, the Operational Multi-scale Environment model with Grid Adaptivity(OMEGA) including an embedded Atmospheric Dispersion Model(ADM), is introduced as a next generation atmospheric simulation system for real-time hazard predictions, such as severe weather or the transport of hazardous release. OMEGA is based on an unstructured grid that can facilitate a continuously varying horizontal grid resolution ranging from 100 km down to 1 km and a vertical resolution from 20 -30 meters in the boundary layer to 1 km in the free atmosphere. OMEGA is also naturally scale spanning and time. In particular, the unstructured grid cells in the horizontal dimension can increase the local resolution to better capture the topography or important physical features of the atmospheric circulation and cloud dynamics. This means the OMEGA can readily adapt its grid to a stationary surface, terrain features, or dynamic features in an evolving weather pattern. While adaptive numerical techniques have yet to be extensively applied in atmospheric models, the OMEGA model is the first to exploit the adaptive nature of an unstructured gridding technique for atmospheric simulation and real-time hazard prediction. The purpose of this paper is to provide a detailed description of the OMEGA model, the OMEGA system, and a detailed comparison of OMEGA forecast results with observed data.