• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1108-1114
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• 2009

Mobility is one of the most important features for a guard robot since it should be operated in rough places. A wheel-based mobile robot capable of jumping is an appropriate structure for a guard robot because it can easily satisfy the requirements for small guard robots. The jumping robot can reach a higher place more rapidly than other locomotion methods. This research proposes a small robot equipped with the jumping mechanism based on the conical spring with the variable length endtip. The variable length endtip enables the independent control of the jump force and jump angle which are related to the jump height and jump distance, respectively. Various experiments demonstrated that the proposed jumping mechanism can provide the independent control of jump force and jump angle, and improve the mobility of a small robot to overcome an obstacle. Furthermore, a combination of the jumping mechanism and the PSD sensor to measure the distance to the step enable the jumping robot to autonomously climb stairs.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.93-94
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• 2008

로봇을 개발함에 있어 많이 겪는 어려움 중 하나는 열악한 시뮬레이션 환경 및 소프트웨어 개발이다. Microsoft사(社)의 MSRDS(Microsoft Robotics Developer Studio)는 3D시뮬레이션 환경과 로봇 구동을 위한 각종 표준화된 서비스들을 지원함으로써 이러한 문제점들을 해결할 수 있다. 본 논문에서는 원자력 발전소의 중 저준위 폐기물 저장창고 검사 로봇을 대상으로 MSRDS를 이용하여 3D 시뮬레이션 및 온라인 피드백 제어를 수행하였다. 로봇은 사륜으로 이루어져 있으며, 주행 환경 확인을 위한 카메라, 장애물 감시용 LRF(Laser Range Finer)센서, 주변 환경 감지를 위한 온도센서, 습도센서 및 MSRDS가 장착된 산업용 3D가 탑재되어 있다. MSRDS의 제어신호는 이벤트로 생성되어 3D 시뮬레이션 렌더링 시간과 동기화되며, Brick 서비스를 통해 전송된다. 피드백은 10ms 주기로 LRF 센서, Motor 엔코더 값을 받아 3D 시뮬레이션에 반영된다. 본 논문에서는 MSRDS의 시뮬레이션 및 실제 로봇과의 동기화 방식을 제시하며 구동 실험으로 검증하였다.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.63 no.7
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• pp.987-993
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• 2014

Pitching machines have been around for many years for casual amusement purpose or professional athletes' training usage, and so forth. The current pitching machines are usually built on the firm ground and do not have any mobility function. In this paper, we develop a pitching machine that has both ball-shooting and mobility functions. Our developed pitching machine consists of two parts. The upper body part has a function of shooting a ball using two DC motors and the lower body part has a function of mobility like mobile robots by using two wheels governed by DC motors. All these functions are operated wirelessly by Android smartphones via bluetooth. The control of each DC motor is done by ${\epsilon}$-PID control method in which the gain tuning is simplied by using a single parameter ${\epsilon}$. Simulation and actual experiment show that our developed pitching machine has both nontrivial shooting and mobility features.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.11
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• pp.1265-1271
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• 2011

These days the number of aged and disabled people is increasing rapidly. But most of the disabled or the aged who have the ability to work, want to engage in economic activities and solve social restrictions as well as their bad financial conditions. This paper concerns about the tracking control of an electric wheelchair robot for welfare vehicle where the seat and electric wheelchair are separated and electric wheelchair robot must be autonomously controlled without the help of assistant. So the aged or the disabled people can drive welfare vehicle by himself by adopting this system. Therefore the concept of both an autonomous driving of electric wheelchair and path tracking robots is required in this system. Finally we suggested fuzzy controller in order to control the path tracking of electric wheelchair robot and compared the capability of the proposed controller with conventional PID controller.

• Journal of Sensor Science and Technology
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• v.29 no.5
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• pp.348-353
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• 2020

This paper presents an adaptive method to avoid obstacles in various environmental settings, using a two-dimensional (2D) LiDAR sensor for mobile robots. While the conventional reaction based smooth nearness diagram (SND) algorithms use a fixed safety distance criterion, the proposed algorithm autonomously changes the safety criterion considering the obstacle density around a robot. The fixed safety criterion for the whole SND obstacle avoidance process can induce inefficient motion controls in terms of the travel distance and action smoothness. We applied a multinomial logistic regression algorithm, softmax regression, to classify 2D LiDAR point clouds into seven obstacle structure classes. The trained model was used to recognize a current obstacle density situation using newly obtained 2D LiDAR data. Through the classification, the robot adaptively modifies the safety distance criterion according to the change in its environment. We experimentally verified that the motion controls generated by the proposed adaptive algorithm were smoother and more efficient compared to those of the conventional SND algorithms.

• The Journal of Korea Robotics Society
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• v.15 no.4
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• pp.375-384
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• 2020

Today's robots consist of many hardware and software subsystems, depending on the functions needed for specific tasks. Integration of subsystems can require a great deal of effort, as both the communication method and protocol of the subsystem can vary. This paper proposes an expandable robotic system in which all subsystems are integrated under Robot Operation System (ROS) framework. To achieve this, the paper presents a software library, ROS_M, developed to implement the TCP/IP-based ROS communication protocol in different control environments such as MCU and RT kernel based embedded system. Then, all the subsystem including hardware can use ROS protocol consistently for communication, which makes adding new software or hardware subsystems to the robotic system easier. A latency measurement experiment reveals that the system built for loop control can be used in a soft real-time environment. Finally, an expandable mobile manipulator robot is introduced as an application of the proposed system. This robot consists of four subsystems that operate in different control environments.

• The Journal of Korea Robotics Society
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• v.8 no.4
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• pp.283-291
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• 2013

Methods for measuring or estimating of ground shape by a laser range finder and a vision sensor(exteroceptive sensors) have critical weakness in terms that these methods need prior database built to distinguish acquired data as unique surface condition for driving. Also, ground information by exteroceptive sensors does not reflect the deflection of ground surface caused by the movement of UGVs. Thereby, UGVs have some difficulties regarding to finding optimal driving conditions for maximum maneuverability. Therefore, this paper proposes a method of recognizing exact and precise ground shape using Inertial Measurement Unit(IMU) as a proprioceptive sensor. In this paper, firstly this method recognizes attitude of a robot in real-time using IMU and compensates attitude data of a robot with angle errors through analysis of vehicle dynamics. This method is verified by outdoor driving experiments of a real mobile robot.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.74-79
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• 2005

In this paper, we propose a novel approach to decentralized motion planning and conflict-resolution for multiple mobile agents working in an environment with unexpected moving obstacles. Our proposed motion planner has two characteristics. One is a real-time collision prognosis based on modified collision map. Collision map is a famous centralized motion planner with low computation load, and the collision prognosis hands over these characteristics. And the collision prognosis is based on current robots status, maximum robot speeds, maximum robot accelerations, and path information produced from off-line path planning procedure, so it is applicable to motion planner for multiple agents in a dynamic environment. The other characteristic is that motion controller architecture is based on potential field method, which is capable of integrating robot guidance to the goals with collision avoidance. For the architecture, we define virtual obstacles making delay time for collision avoidance from the real-time collision prognosis. Finally the results obtained from realistic simulation of a multi-robot environment with unknown moving obstacles demonstrate safety and efficiency of the proposed method.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1657-1661
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• 2005

The velocity dipole field method is presented for real-time collision avoidance of mobile robots. The direction of motion of the obstacle is used as the axis of the dipole field, and the speed of the obstacle is used to proportionally strengthen the dipole field. The elliptical field lines of the dipole field are useful to skillfully guide the robot around obstacles, quite similar to the way humans avoid moving obstacles. Field modulation coefficient is also introduced to weaken the field effect as the obstacle recedes. The real-time algorithm of the velocity dipole field has been devised and experimentally tested on the robot soccer test-bed. The results show the capability of the new real-time collision avoidance strategy and how it can overcome the weaknesses in the conventional potential field method. The new method makes an explicit and proactive action of collision avoidance, unlike the conventional method, which forces the robot merely away from the obstacle aimlessly. The proposed method delivers greater capability with no considerable computational overhead

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.4
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• pp.372-378
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• 2013

In this paper, we research the localization problem of the crawler-type inspection robot for underwater structure which travels an outer wall of underwater structure. Since various factors of the underwater environment affect an encoder odometer, it is hard to localize robot itself using only on-board sensors. So in this research we used a depth sensor and an IMU to compensate odometer which has extreme error in the underwater environment through using Extended Kalman Filter(EKF) which is normally used in mobile robotics. To acquire valid measurements, we implemented precision sensor modeling after assuming specific situation that robot travels underwater structure. The depth sensor acquires a vertical position of robot and compensates one of the robot pose, and IMU is used to compensate a bearing. But horizontal position of robot can't be compensated by using only on-board sensors. So we proposed a localization algorithm which makes horizontal direction error bounded by using kinematics relationship. Also we implemented computer simulations and experiments in underwater environment to verify the algorithm performance.