• 제어로봇시스템학회논문지
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• 제7권1호
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• pp.1187-1195
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• 2001

This paper presents a sweeping path planning algorithm for an autonomous smearing robot. An automatic planner generates a sweeping path pattern by proposed five basic procedures. This algorithm rocog-nizes obstacle on the architectural CAD draft and generates subgoals as tracking points which executes the area filling task based on heuristic approach. A sweeping path is planned by sequentially connecting the track-ing points in such a way that(1) the connected line segments should not be crossed, (2) the total tracking points should be as short as possible, and (3) the tracking line should not pass through the obstacle, Feasibility of the developed techniques has been demonstrated on a real architectural CAD draft.

• 제어로봇시스템학회논문지
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• 제18권3호
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• pp.267-274
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• 2012

We proposed the KPP (Korea university Path Planner) in our previous works. The KPP is the path planning scheme of a car-like mobile robot in parking environment. The objective of this paper is to investigate the advantage of the KPP through the quantitative and qualitative analysis compared with conventional RRT. For comparison, we proposed travel time for performance index. This paper shows that the KPP shows outstanding performances from the viewpoint of travel time and computational efficiency compared with RRT.

• 전자공학회논문지 IE
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• 제47권2호
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• pp.66-72
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• 2010

자율적인 다중이동 로봇환경에서는 현시점에서 목표점까지 장애물과 충돌없이 연결하는 최적 경로를 설정하는 것은 필수불가결하며 매우 중요하다. 실제 많은 이동로봇은 주위 장애물에 대하여 주어진 정보 없이 미지의 환경에서 자율적 이동이 가능해야 한다. 따라서 본 논문에서는 다중이동 로봇환경에 적합한 새로운 형태의 충돌회피 최적경로에 대한 방법을 연구한다. 잘 알려진 포텐셜필드 방법을 이용하여 다중이동 로봇의 전역경로를 계획하고, 퍼지로직 시스템을 이용하여 각 로봇에 근접하는 혹은 경로를 가로막는 장애물과의 충돌을 피하기 위한 지역경로를 계획한다. 제안된 방법의 성능 및 정확성을 검증하기 위해 다양한 모의실험을 진행하여 결과를 검증하고 이의 결과를 토의한다.

• International Journal of Control, Automation, and Systems
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• 제5권6호
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• pp.674-680
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• 2007

The probabilistic roadmap (PRM) method, which is a popular path planning scheme, for a manipulator, can find a collision-free path by connecting the start and goal poses through a roadmap constructed by drawing random nodes in the free configuration space. PRM exhibits robust performance for static environments, but its performance is poor for dynamic environments. On the other hand, reinforcement learning, a behavior-based control technique, can deal with uncertainties in the environment. The reinforcement learning agent can establish a policy that maximizes the sum of rewards by selecting the optimal actions in any state through iterative interactions with the environment. In this paper, we propose efficient real-time path planning by combining PRM and reinforcement learning to deal with uncertain dynamic environments and similar environments. A series of experiments demonstrate that the proposed hybrid path planner can generate a collision-free path even for dynamic environments in which objects block the pre-planned global path. It is also shown that the hybrid path planner can adapt to the similar, previously learned environments without significant additional learning.

• 제어로봇시스템학회논문지
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• 제21권3호
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• pp.257-264
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• 2015

This paper proposes an adaptive RRT (Rapidly-exploring Random Tree) for path planning of high DOF multibody robotic system. For an efficient path planning in high-dimensional configuration space, the proposed algorithm adaptively selects the robot bodies depending on the complexity of path planning. Then, the RRT grows only using the DOFs corresponding with the selected bodies. Since the RRT is extended in the configuration space with adaptive dimensionality, the RRT can grow in the lower dimensional configuration space. Thus the adaptive RRT method executes a faster path planning and smaller DOF for a robot. We implement our algorithm for path planning of 19 DOF robot, AMIRO. The results from our simulations show that the adaptive RRT-based path planner is more efficient than the basic RRT-based path planner.

• 한국군사과학기술학회지
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• 제15권4호
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• pp.424-434
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• 2012

This paper presents a path planning algorithm of the unmanned aerial vehicle for the neutralization of the enemy firepower. The long range firepower of the ememy is usually located at the rear side of the mountain which is difficult to bomb. The path planner not only consider the differential constraints of the Unmanned Aerial Vehicle (UAV) but also consider the final approaching angle constraint. This problem is easily solved by incorporating the analytical upper bounded continuous curvature path smoothing algorithm into the Rapidly Exploring Random Tree (RRT) planner. The proposed algorithm can build a feasible path satisfying the kinematic constraints of the UAV on the fly. In addition, the curvatures of the path are continuous over the whole path. Simulation results show that the proposed algorithm can generate a feasible path of the UAV for the bombing mission regardless of the posture of the tunnel.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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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.

• 전자공학회논문지B
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• 제33B권7호
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• pp.1-10
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• 1996

There are many challenging problems in mobile robot navigation. As an example, a mobile robot may wander around in local minimum and may wiggle when it moves through a narrow corridor. In addition, the real time obstacle avoidance and the posture control of mobile robot are also very improtant problems. To address these problems, a navigation algorithm which is composed o freal time obstacle avoidance algorithm and a global path planner (GPP) that genrates the shortest path is presented. In this paper, the global path planner reduce the calculation time by reducing the dta to be handled. Also it can make a real time obstacle avoidance by using the fuzzy logic inference. So the presented algorithm provide a stable navigastion for the mobile robot when it fall into the unstable navigation.

• Journal of Construction Engineering and Project Management
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• 제6권2호
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• pp.30-39
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• 2016

This research presents the development of a self-governing mobile robot navigation system for indoor construction applications. This self-governing robot navigation system integrated robot control units, various positioning techniques including a dead-reckoning system, a UWB platform and motion sensors, with a BIM path planner solution. Various algorithms and error correction methods have been tested for all the employed sensors and other components to improve the positioning and navigation capability of the system. The research demonstrated that the path planner utilizing a BIM model as a navigation site map could effectively extract an efficient path for the robot, and could be executed in a real-time application for construction environments. Several navigation strategies with a mobile robot were tested with various combinations of localization sensors including wheel encoders, sonar/infrared/thermal proximity sensors, motion sensors, a digital compass, and UWB. The system successfully demonstrated the ability to plan an efficient path for robot's movement and properly navigate through the planned path to reach the specified destination in a complex indoor construction site. The findings can be adopted to several potential construction or manufacturing applications such as robotic material delivery, inspection, and onsite security.

• 한국생산제조학회지
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• 제24권4호
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• pp.441-447
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• 2015

This paper proposes a novel fuzzy-based multi-criteria decision making method and implements a footstep planner for humanoid robots with it. Humanoid robots require additional footstep planning process in addition to path planning for the autonomous navigation. Moreover, it is necessary to consider safety and energy consumption as well as path efficiency and multi-criteria decision making is indispensable. The proposed method can provide not only well- distributed and non-dominated, but also more preferable solutions for users. The planned footsteps by the proposed method were verified through simulation. The results indicate that the user's preference is properly reflected in optimized solutions maintaining solution quality.