• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2408-2410
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• 2003

본 논문에서는 여러 대의 모바일 로봇을 이용해 미지의 환경에 대한 맵핑을 보다 빠르고 효율적으로 행할 수 있는 방법을 제시한다. 각각의 모바일 로봇은 충돌 회피, 경로 설정 등의 기능 이외에 서버와의 통신 및 로봇간의 통신을 통해 맵핑에 관한 정보를 공유해 빠른 시간이내에 신뢰할만한 맵핑을 행할 수 있고 서버에서의 명령을 통해 부가적인 기능을 수행할 수 있다. 여러 대의 모바일 로봇을 이용한 맵핑에서 가장 중요한 것은 신뢰할만한 Navigation 이다. 이를 위해 엔코더와 ONS(Optical Navigation System)을 이용해 정확한 Localization을 행하였으며, 초음파 센서를 이용해 장애물의 위치 및 거리를 파악해 미지의 영역에 대한 맵핑을 수행하였다. 제안된 방법의 검증을 위해 시뮬레이션을 행하였다.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.3
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• pp.507-514
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• 2022

Mobile manipulators are getting lime light in the field of home automation due to their mobility and manipulation capabilities. In this paper, we developed a small size manipulator system that can be mounted on a mobile robot as a preliminary study to develop a mobile manipulator. The developed manipulator has four degree-of-freedom. At the end-effector of manipulator, there are a camera and a gripper to recognize and manipulate the object. One of four degree-of-freedom is linear motion in vertical direction for better interaction with human hands which are located higher than the mobile manipulator. The developed manipulator was designed to dispose the four actuators close to the base of the manipulator to reduce rotational inertia of the manipulator, which improves stability of manipulation and reduces the risk of rollover. The developed manipulator repeatedly performed a pick and place task and successfully manipulate the object within the workspace of manipulator.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.40 no.8
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• pp.703-710
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• 2016

In robotics research, accurate estimation of current robot position is important to achieve motion control of a robot. In this research, we focus on a sensor fusion method to provide improved position estimation for a wheeled mobile robot, considering two different sensor measurements. In this case, we fuse camera-based vision and encode-based odometry data using Kalman filter techniques to improve the position estimation of the robot. An external camera-based vision system provides global position coordinates (x, y) for the mobile robot in an indoor environment. An internal encoder-based odometry provides linear and angular velocities of the robot. We then use the position data estimated by the Kalman filter as inputs to the motion controller, which significantly improves performance of the motion controller. Finally, we experimentally verify the performance of the proposed sensor fused position estimation and motion controller using an actual mobile robot system. In our experiments, we also compare the Kalman filter-based sensor fused estimation with two different single sensor-based estimations (vision-based and odometry-based).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1817-1825
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• 2021

Omnidirectional mobile robots can be mobile in any direction without changing the robot's direction, making them easy to apply in many applications and providing excellent maneuverability. Omnidirectional mobile robots have non-linear dynamic components such as friction, making them difficult to model accurately. In this paper, we linearize the mobile robot system using the mobile robot's inverse dynamics and integral sliding mode control method to remove these nonlinear components. And the position and velocity gains are optimized using a genetic algorithm to realize the optimal performance of the proposed system control method. As a result of the performance evaluation, the genetic algorithm's control method showed superior performance than the control method with an arbitrary gain. And the proposed inverse dynamic and integral sliding mode control method can be applied to other control methods. It can be beneficial for designing a linear control system.

• Proceedings of the Korean Society of Computer Information Conference
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• 2009.01a
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• pp.125-128
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• 2009

모바일 로봇이 자기 역할을 수행하기 위해서는 자기위치인식 기술이 반드시 필요하다. 이에 본 논문에서는 기존 초음파 센서만을 이용한 위치인식 기술의 난제와 카메라 즉, 영상처리만을 이용한 위치 인식 기술의 난제를 두 가지 기술의 융합으로 쉽게 해결할 수 있도록 한다.

• Journal of the Institute of Convergence Signal Processing
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• v.9 no.3
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• pp.230-237
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• 2008

Recently, lots of interest and competition in developments related to the autonomous-vehicle robot are being further increased. However, the absence of the standard architectures for effectively controlling the autonomous-vehicle robot led to many difficulties such as the long duration of development and the uncompatibility with other autonomous-vehicle robots. Accordingly, we implemented a mobile autonomous-vehicle robot system based on JAUS standard architecture. The mobile robot communicates with the remote-control system by using wireless LAN UDP/IP JAUS command massages. Its effectiveness is showed through the experimental results related to the navigation of implemented robot.

• Proceedings of the Korea Information Processing Society Conference
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• 2016.10a
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• pp.775-778
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• 2016

로봇 주행 기술은 전통적인 로봇요소 기술 외에도 여러 기술로 대상 응용서비스에 따라 IT 기술과 적극적인 융합을 통해 다양한 주행방법과 주행성능이 향상되고 있다. 본 논문에서는 대표적인 실내 모바일 로봇인 로봇 청소기를 대상으로 기존의 방법인 적외선과 카메라 방법이 아닌 보통 가정에도 쉽게 존재하는 AP를 이용해 목표를 설정하여 포섭구조 이론을 기반으로 동적인 환경에서도 충전 스테이션 까지 자율 주행이 가능한 로봇 알고리즘을 설계하였다. 그 결과 동적인 환경을 설정하여 로봇이 AP를 찾아가는 것을 확인하였고 주행 경로와 경과 시간을 표로 도출하여 다른 경우를 예측할 수 있게 하였다. 향후 행동 기반 로봇과 다양한 센서를 이용하여 로봇의 위치와 목표점 사이의 최단거리 경로를 구하여 주행하는 것이 목표이다.

• Journal of the Korea Society of Computer and Information
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• v.18 no.1
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• pp.11-19
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• 2013

For an autonomous multi-mobile robot system, path planning and collision avoidance are important functions used to perform a given task collaboratively and cooperatively. This study considers these important and challenging problems. The proposed approach is based on a potential field method and fuzzy logic system. First, a global path planner selects the paths of the robots that minimize the cost function from each robot to its own target using a potential field. Then, a local path planner modifies the path and orientation from the global planner to avoid collisions with static and dynamic obstacles using a fuzzy logic system. In this paper, each robot independently selects its destination and considers other robots as dynamic obstacles, and there is no need to predict the motion of obstacles. This process continues until the corresponding target of each robot is found. To test this method, an autonomous multi-mobile robot simulator (AMMRS) is developed, and both simulation-based and experimental results are given. The results show that the path planning and collision avoidance strategies are effective and useful for multi-mobile robot systems.

• Journal of IKEEE
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• v.25 no.2
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• pp.337-343
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• 2021

Deep reinforcement learning is an artificial intelligence algorithm that enables learners to select optimal behavior based on raw and, high-dimensional input data. A lot of research using this is being conducted to create an optimal movement path of a mobile robot in an environment in which obstacles exist. In this paper, we selected the Dueling Double DQN (D3QN) algorithm that uses the prioritized experience replay to create the moving path of mobile robot from the image of the complex surrounding environment. The virtual environment is implemented using Webots, a robot simulator, and through simulation, it is confirmed that the mobile robot grasped the position of the obstacle in real time and avoided it to reach the destination.

• Proceedings of the Korean Society of Computer Information Conference
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• 2010.07a
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• pp.51-54
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• 2010

본 논문에서는 포텐셜 필드 방법과 퍼지로직 시스템을 이용하여 멀티 모바일 로봇의 충돌회피를 위한 경로계획을 연구한다. 잘 알려진 포텐셜 필드 방법은 멀티 모바일 로봇 시스템에 있어서 각각의 로봇에 대한 전역경로를 계획하기 위해 사용되었으며, 퍼지로직 시스템은 각 로봇에 근접하는 혹은 진행하는 로봇의 경로를 가로막는 장애물과의 충돌을 피하고 안전하게 목적지에 도달하기 위한 지역경로를 계획하기 위해 이용되었다.