• 전자공학회논문지B
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• 제31B권4호
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• pp.40-47
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• 1994

In this paper, Micro-Genetic algorithms($\mu$-GAs) is proposed on a minimum-time path planning for robot manipulator. which is a kind of optimization algorithm. The minimum-time path planning, which can allow the robot system to perform the demanded tasks with a minimum execution time, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computation burden and can`t often find the optimaul values. One way to overcome such difficulties is to apply the Micro-Genetic Algorithms, which can allow to find the optimul values, to the minimum-time problem. This paper propose an approach for solving the minimum-time path planning by using Micro-Genetic Algorithms. The effectiveness of the proposed method is demonstrated using the 2 d.o.f plannar Robot manipulator.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1990년도 하계학술대회 논문집
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• pp.485-491
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• 1990

We propose a minimum-time path planning soheme for the robot manipulator using Hopfield neural network. The minimum-time path planning, which can allow the robot system to perform the demanded tasks with a minimum execution time, may be of consequence to improve the productivity. But most of the methods proposed till now suffers from a significant computational burden and thus limits the on-line application. One way to avoid such a difficulty is to apply the neural network technique, which can allow the parallel computation, to the minimum-time problem. This paper propose an approach for solving the minimum-time path planning by using Hopfield neural network. The effectiveness of the proposed method is demonstrarted using the PUMA 560 manipulator.

• 한국자동차공학회논문집
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• 제2권6호
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• pp.57-65
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• 1994

A collision-free path planning algorithm between an articulated robot and polyhedral obstacles using configuration space is presented. In configuration space, a robot is treated as a point and obstacles are treated as grown forbidden regions. Hence path planning problem is transformed into moving a point from start position to goal position without entering forbidden regions. For mapping to 3D joint space, slice projection method is used for first revolute joint and inverse kinematics is used for second and third revolute joint considering kinematic characteristics of industrial robot. Also, three projected 2D joint spaces are used in search of collision-free path. A proper example is provided to illustrate the proposed algorithm.

• Journal of Biosystems Engineering
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• 제24권4호
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• pp.301-308
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• 1999

Path planning for field operation of agricultural machinery is an indispensible part for precision farming or autonomous field operation. In this study, two algorithms (I, II) of generating a time-based shortest operation path were suggested to plan an optimal operation of an agricultural tractor-implement in a rectangular shaped field. The algorithms were based on modification of a minimum spanning tree algorithm, and applied for tractor-implement operations. the generated path was consisted of round operation and returning operation sections. The number of round operation was determined from the condition that a tractor can turn smoothly at headlands. The performance of the algorithms was evaluated by the calculation number for path generation and the total path length generated. Their stability was affected by the number of returning operation, but the algorithm II was considered to be more stable. In addition, the performances of the developed algorithms were compared with those of the conventional field operations at selected field sizes and shapes. The results showed that the algorithms could reduce field operation time greatly. For a 100m$\times$40m field, the reduced path length was 78m. The study also included an user interface program for implementing the algorithms and generating GPS coordinates that could be used in GIS softwares for precision farming.

• 한국지능시스템학회논문지
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• 제18권1호
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• pp.7-13
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• 2008

이 논문은 이동 에이전트의 경로 계획 알고리듬을 제안한다. 이동 에이전트에 대한 경로 계획은 많은 연구가 수행되어왔지만 복잡한 주변 환경에 대한 경로 계획에서의 시-공간적 제약조건은 수학적으로 모델화하기 어려우며, 최적해를 구하기는 쉽지 않다. 이 논문에서 그래픽 기반의 최적 경로 계획 알고리듬을 제안한다. 작업 환경은 에이전트가 이동할 수 있는 자유영역과 장애물 등이 존재하는 이동 불가 영역으로 구분하고, 자유 이동 영역 내에서 최적 경로는 개미집단-최적화 알고리듬을 이용한 탐색으로부터 구한다.

• 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.

• 한국해양공학회지
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• 제33권6호
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• pp.510-517
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• 2019

Efficient path planning is essential for unmanned surface vehicle (USV) navigation. The A^* algorithm is an effective algorithm for identifying a safe path with optimal distance cost. In this study, a modified version of the A^* algorithm is applied for planning the path of a USV in a static and dynamic obstacle environment. The current study adopts the A^* approach while maintaining a safe distance between the USV and obstacles. Two important parameters-path length and computational time-are considered at various start times. The results demonstrate that the modified approach is effective for obstacle avoidance by a USV that is compliant with the International Regulations for Preventing Collision at Sea (COLREGs).

• 한국군사과학기술학회지
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• 제24권1호
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• pp.61-69
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• 2021

Recently, autonomous navigation technology is actively being developed due to the increasing demand of an unmanned surface vehicle(USV). Local planning is essential for the USV to safely reach its destination along paths. the dynamic window approach(DWA) algorithm is a well-known navigation scheme as a local path planning. However, the existing DWA algorithm does not consider path line tracking, and the fixed weight coefficient of the evaluation function, which is a core part, cannot provide flexible path planning for all situations. Therefore, in this paper, we propose a new DWA algorithm that can follow path lines in all situations. Fixed weight coefficients were trained using reinforcement learning(RL) which has been actively studied recently. We implemented the simulation and compared the existing DWA algorithm with the DWA algorithm proposed in this paper. As a result, we confirmed the effectiveness of the proposed algorithm.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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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.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.900-903
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• 1996

The objective of this paper is to make the weighted graph map for path planning using the ultrasonic sensor measurements that are acquired when an A.M.R (autonomous mobile robot) explores the unknown circumstance. First, The A.M.R navigates on unknown space with wall-following and gathers the sensor data from the environments. After this, we constructs the occupancy grid map by interpreting the gathered sensor data to occupancy probability. For the path planning of roadmap method, the weighted graph map is extracted from the occupancy grid map using morphological image processing and thinning algorithm. This methods is implemented on an A.M.R having a ultrasonic sensor.