• 한국지능시스템학회논문지
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• 제18권4호
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• pp.566-571
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• 2008

본 논문에서는 Particle Swarm Optimization(PSO) 기법을 이용한 이족보행로봇의 보행 계획 방법을 제안한다. 이족보행로봇의 보행 프리미티브를 기반으로 PSO의 학습 및 군집 특성을 이용하여 장애물이 있는 2차원 작업공간에서 보행 계획 방법을 설계하였다. 먼저 PSO의 탐색알고리즘을 사용하여 장애물을 회피하는 실행 가능한 보행 프리미티브들의 순서를 찾아서 보행 경로를 생성하고, 탐색된 경로를 바탕으로 보행 걸음수와 이동 거리를 최적화 하는 경로 최적화 알고리즘을 제안하였다. 제안된 보행 계획방법은 다양한 구성의 장애물을 포함한 작업환경에서 모의실험을 통하여 발걸음 탐색 시간이 줄고 최적화된 보행 경로를 생성하는 것을 검증하였다.

• 로봇학회논문지
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• 제17권4호
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• pp.407-416
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• 2022

Multiple AMRs have been proved to be effective in improving warehouse productivity by eliminating workers' wasteful walking time. Although Multi-agent Path Finding (MAPF)-based solution is an optimal approach for this task, its deployment in practice is challenging mainly due to its imperfect plan-execution capabilities and insufficient computing resources for high-density environments. In this paper, we present a MAPF-based fleet management system architecture that robustly manages multiple robots by re-computing their paths whenever it is necessary. To achieve this, we defined four events that trigger our MAPF solver framework to generate new paths. These paths are then delivered to each AMR through ROS2 message topic. We also optimized a graph structure that effectively captures spatial information of the warehouse. By using this graph structure we can reduce computational burden while keeping its rescheduling functionality. With proposed MAPF-based fleet management system, we can control AMRs without collision or deadlock. We applied our fleet management system to the real logistics warehouse with 10 AMRs and observed that it works without a problem. We also present the usage statistic of adopting AMRs with proposed fleet management system to the warehouse. We show that it is useful over 25% of daily working time.

• 전기학회논문지
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• 제67권2호
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• pp.285-292
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• 2018

In this paper, we propose a distributed search of a cluster robot using tree structure in an unknown environment. In the proposed method, the cluster robot divides the unknown environment into 4 regions by using the LRF (Laser Range Finder) sensor information and divides the maximum detection distance into 4 regions, and detects feature points of the obstacle. Also, we define the detected feature points as Voronoi Generators of the Voronoi Diagram and apply the Voronoi diagram. The Voronoi Space, the Voronoi Partition, and the Voronoi Vertex, components of Voronoi, are created. The generated Voronoi partition is the path of the robot. Voronoi vertices are defined as each node and consist of the proposed tree structure. The root of the tree is the starting point, and the node with the least significant bit and no children is the target point. Finally, we demonstrate the superiority of the proposed method through several simulations.

• 정보처리학회논문지:소프트웨어 및 데이터공학
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• 제4권3호
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• pp.135-142
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• 2015

소프트웨어가 경쟁력의 핵심이 되는 소프트웨어 중심 사회로 이행되면서 프로그래밍 교육의 중요성이 새롭게 부각되고 있다. 세계적인 조기 코딩 교육 열풍도 이러한 추세를 반영하고 있으나 이를 지원하기 위한 교육 환경에서는 클라우드 컴퓨팅과 같은 새로운 컴퓨팅 환경을 효과적으로 활용함에 제약이 있는 것이 현실이다. 본 논문에서는 클라우드 환경에서 모바일 기기와 로봇을 이용하여 손쉽게 소프트웨어를 개발하고 프로그래밍 교육을 할 수 있는 클라우드 기반 지식 공유 및 제어 시스템인 클라우드보드(Cloudboard)를 제안한다. 특히 군집 로봇 시스템에서 개별 로봇의 센서 정보를 다수의 로봇이 공유하고 협업하여 공동 임무를 수행하도록 할 경우 클라우드보드 기능을 이용하여 손쉽게 프로그램을 개발하여 교육에 활용할 수 있음을 보인다. 클라우드보드의 기능은 기존의 대표적인 아키텍처 패턴을 비교 분석한 결과를 토대로 설계되었으며 실험적으로 효과와 성능을 검증한다.

• 말소리와 음성과학
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• 제11권3호
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• pp.39-47
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• 2019

본 논문에서는 대량의 음성 데이터를 이용하여 기존의 음소 세트를 확장하여 자유발화 음성인식기의 성능을 향상시키는 방법을 제안한다. 제안된 방법은 먼저 방송 데이터에서 가변 길이의 음소 세그먼트를 추출한 다음 LSTM 구조를 기반으로 고정 길이의 잠복벡터를 얻는다. 그런 다음, k-means 군집화 알고리즘을 사용하여 음향적으로 유사한 세그먼트를 군집시키고, Davies-Bouldin 지수가 가장 낮은 군집 수를 선택하여 새로운 음소 세트를 구축한다. 이후, 음성인식기의 발음사전은 가장 높은 조건부 확률을 가지는 각 단어의 발음 시퀀스를 선택함으로써 업데이트된다. 새로운 음소 세트의 음향적 특성을 분석하기 위하여, 확장된 음소 세트의 스펙트럼 패턴과 세그먼트 지속 시간을 시각화하여 비교한다. 제안된 단위는 자유발화뿐만 아니라, 낭독체 음성인식 작업에서 음소 단위 및 자소 단위보다 더 우수한 성능을 보였다.

• 제어로봇시스템학회논문지
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• 제6권8호
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• pp.659-665
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• 2000

In this paper a platoon merging control system is considered as a remotely located system with state represented by a stochastic process. in the system it is common to encounter situations where a single decision maker controls a large number of subsystems and observation and control signals are sent over a communication channel with finite capacity and significant transmission delays. Unlike a classical estimation problem where the observation is a continuous process corrupted by additive noise there is a constraint that the observation must be coded and transmitted over a digital communication channel with fintie capacity. A recursive coder-estimator sequence is a state estimation scheme based on observations transmitted with finite communication capacity constraint. in this paper we introduce a stochastic model for the lead vehicle in a platoon of vehicles in a lane considering the angle between the road surface and a horizontal plane as a stochastic process. In order to merge two platoons the lead vehicle of the following platoon is controlled by a remote control station. Using the observation transmitted over communication channel the remote control station designs the feedback controller. The simulation results show that the intervehicle spacings and the deviations from the desired intervehicle spacing are well regulated.

• 제어로봇시스템학회논문지
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• 제18권4호
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• pp.353-358
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• 2012

Human detection is a challenging task in many fields because it is difficult to detect humans due to their variable appearance and posture. Furthermore, it is also hard to track the detected human because of their dynamic and unpredictable behavior. The evaluation speed of method is also important as well as its accuracy. In this paper, we propose unified detection and tracking method for humans using Gaussian-PSO (Gaussian Particle Swarm Optimization) with the HOG (Histograms of Oriented Gradients) features to achieve a fast and accurate performance. Keeping the robustness of HOG features on human detection, we raise the process speed in detection and tracking so that it can be used for real-time applications. These advantages are given by a simple process which needs just one linear-SVM classifier with HOG features and Gaussian-PSO procedure for the both of detection and tracking.

• 제어로봇시스템학회논문지
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• 제7권6호
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• pp.477-486
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• 2001

Many physical systems can be modeled by incorporating continuous and discrete event nature together. Such hybrid systems contain both continuous and discrete states that influence the dynamic be-havior of the systems. There has been an increasing interest in thers types of systems during the last dec-ade, mostly due to the growing usage of computers in the control of physical plants but also as a result of the hybrid nature of physical processes. The stability theory for hybrid systems is considered as extension of Lyapunov theory where the existence of an abstract energy function satisfying certain properties verifies stability, called multiple Lyapunov theory. In this paper, a hybrid stabilizing controller is proposed using the control Lyapunov function method and multiple Lyapunov theory, and the proposed method is applied to lon-gitudinal spacing control in a vehicle platoon for intelligent transportation systems(ITS).

• 로봇학회논문지
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• 제14권4호
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• pp.285-292
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• 2019

Path planning is an important problem to solve in robotics and there has been many related studies so far. In the previous research, we proposed the Heterogeneous-Ants-Based Path Planner (HAB-PP) for the global path planning of mobile robots. The conventional path planners using grid map had discrete state transitions that constrain the only movement of an agent to multiples of 45 degrees. The HAB-PP provided the smoother path using the heterogeneous ants unlike the conventional path planners based on Ant Colony Optimization (ACO) algorithm. The planner, however, has the problem that the optimization of the path once found is fast but it takes a lot of time to find the first path to the goal point. Also, the HAB-PP often falls into a local optimum solution. To solve these problems, this paper proposes an improved ant-inspired path planner using the Rapidly-exploring Random Tree-star ($RRT^*$). The key ideas are to use $RRT^*$ as the characteristic of another heterogeneous ant and to share the information for the found path through the pheromone field. The comparative simulations with several scenarios verify the performance of the improved HAB-PP.

• 로봇학회논문지
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• 제14권4호
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• pp.301-310
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• 2019

A new algorithm has been propose to detect the reflected light region as disturbances in a real-time vision system. There have been several attempts to detect existing reflected light region. The conventional mathematical approach requires a lot of complex processes so that it is not suitable for a real-time vision system. On the other hand, when a simple detection process has been applied, the reflected light region can not be detected accurately. Therefore, in order to detect reflected light region for a real-time vision system, the detection process requires a new algorithm that is as simple and accurate as possible. In order to extract the reflected light, the proposed algorithm has been adopted several filter equations and clustering processes in the HSI (Hue Saturation Intensity) color space. Also the proposed algorithm used the pre-defined reflected light data generated through the clustering processes to make the algorithm simple. To demonstrate the effectiveness of the proposed algorithm, several images with the reflected region have been used and the reflected regions are detected successfully.