• The Transactions of the Korean Institute of Electrical Engineers D
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• v.51 no.12
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• pp.583-595
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• 2002

Homing operation can be defined as a series of actions which are necessary for a mobile robot to move from the current position with any arbitrary orientation to a desired position with a specified orientation, while avoiding possible obstacles. In this paper, a homing and obstacle avoidance algorithm for nonholonomic mobile robots is proposed. The proposed algorithm consists of a local goal generator, a discrete state controller, and local path tracking controller based on Aicardi's path following algorithm. In the discrete state controller, 4 states are defined according to the environmental conditions and 4 desired high-level command for the states are given as follows: avoid, wander, home and homing zones. The proposed local goal generator is designed to generate the desired local path by using weighted distance transforms which are newly made to satisfy the nonholonomic constraints of mobile robots. Here, subgoals are also found as vertices of the desired local path. To demonstrate result effectiveness and applicability of the proposed algorithm, computer simulations are illustrated and experimental results for a real mobile robot system are also provided.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.1140-1143
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• 1996

A new approach based on artificial potential function is proposed for the obstacle avoidance of redundant manipulators. Unlike the so-called "global" path planning method, which requires expensive computation for the path search before the manipulator starts to move, this new approach, "local" path planning, researches the path in real-time using the local distance information. Previous use of artificial potential function has exhibited local minima in some complex environments. This thesis proposes a potential function that has no local minima even for a cluttered environment. This potential function has been implemented for the collision avoidance of a redundant robot in Simulation. The simulation also employ an algorithm that eliminates collisions with obstacles by calculating the repulsive potential exerted on links, based on the shortest distance to object.

• ETRI Journal
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• v.43 no.4
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• pp.580-593
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• 2021

When operating in confined spaces or near obstacles, collision-free path planning is an essential requirement for autonomous exploration in unknown environments. This study presents an autonomous exploration technique using a carefully designed collision-free local planner. Using LiDAR range measurements, a local end-point selection method is designed, and the path is generated from the current position to the selected end-point. The generated path showed the consistent collision-free path in real-time by adopting the Euclidean signed distance field-based grid-search method. The results consistently demonstrated the safety and reliability of the proposed path-planning method. Real-world experiments are conducted in three different mines, demonstrating successful autonomous exploration flights in environment with various structural conditions. The results showed the high capability of the proposed flight autonomy framework for lightweight aerial robot systems. In addition, our drone performed an autonomous mission in the tunnel circuit competition (Phase 1) of the DARPA Subterranean Challenge.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2318-2320
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• 1998

A genetic algorithm for global and local path planning and collision avoidance of mobil robot in unstructured workspace is proposed. The genetic algorithm searches for a path in the entire and continuous free space and unifies global path planning and local path planning. The simulation shows the proposed method is an efficient and effective method when compared with the traditional collision avoidance algorithms.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3098-3100
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• 1999

A genetic algorithm for global and local path planning and collision avoidance of mobile robot in dynamic working environment is proposed. The genetic algorithm searches for a path in the entire and continuous free space and unifies global path planning and local path planning. The simulation shows the proposed method is an efficient and effective method when compared with the traditional collision avoidance algorithms.

• Journal of KIISE
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• v.41 no.12
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• pp.1145-1151
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• 2014

In this paper, we propose MPLO(Multi-Path routing with Local Optimization) for load balancing in the tactical backbone network. The MPLO manages global metric and local metric separately. The global metric is propagated to other routers via a routing protocol and is used for configuring loop-free multi-path. The local metric reflecting link utilization is used to find an alternate path when congestion occurs. We verified MPLO could effectively distribute user traffic among available routers by simulation.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1881_1882
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• 2009

Simple quadratic potential functions for unicycle robot path planning are presented, where proposed algorithm for path planning has the different environment for each robot based on LOS(Line Of Sight) between a target and an obstacle, unlike a conventional path planning. In doing so, the proposed algorithm assumes that each swarm robot equips its own vision instead of a ceiling camera. In particular, this paper presents that each robot follows its different local leader. As a result proposed algorithm reduces local minimum problems by the help of each local leader.

• Journal of Communications and Networks
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• v.9 no.4
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• pp.356-367
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• 2007

In large networks, maintaining precise global network state information is impossible. The imprecise network state information has significant impacts on Quality-of-Service(QoS) routing and path establishment. In this paper, we develop analytical models for investigating the QoS routing schemes that are designed to tolerate imprecise network state information, and study the performance of various QoS routing schemes, including randomized routing, multi-path routing, and probability based routing, using both the models and simulations. We further propose a new mechanism, called local rerouting, that improves the effectiveness of QoS path establishment in the presence of imprecise global network state information. Local rerouting is orthogonal to existing schemes for dealing with imprecise state information and can be used in conjunction with them to alleviate the impacts of the imprecise information. The results of our performance study indicate that local rerouting is robust and effective.

• Journal of the Korea Institute of Military Science and Technology
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• v.16 no.6
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• pp.719-725
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• 2013

In this paper, we propose a local path planning method based on RANGER algorithm and autonomy manager for autonomous navigation of UGV in urban environment. LPP method is designed to generate the local path in sensing area by using lane and curb of pavement and autonomy manager is designed to make a decision which transit the status of LPP component to a proper status for current navigation environment. A field test is conducted with scenarios in real urban environment in which crossroad, crosswalk and pavement are included and the performance of proposed method is validated.

• Proceedings of the KIEE Conference
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• 2003.07d
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• pp.2420-2422
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• 2003

In this paper, two Fuzzy Logics for path planning of an autonomous mobile robot are proposed. If a target point is given, such problems regarding the velocity and object recognition are closely related with path to which the mobile robot navigates. Therefore, to ensure safety navigation of the mobile robot for two fuzzy logic parts, path planning considering the surrounding environment was performed in this paper. First, feature points for local and global path are determined by utilizing Cell Decomposition off-line computation. Second, the on-line robot using two Fuzzy Logics navigates around path when it tracks the feature points. We demonstrated optimized path planning only for local path using object recognition fuzzy logic corresponds to domestic situation. Furthermore, when navigating, the robot uses fuzzy logic for velocity and target angle. The proposed algorithms for path planning has been implemented and tested with pioneer-dxe mobile robot.