• 제어로봇시스템학회논문지
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• 제5권7호
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• pp.836-840
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• 1999

Linear motion and angular motion in task space are handled separately in joint velocity planning for redundant robot manipulators. In solving inverse kinematic equations with given joint velocity limits, we consider the order of priority for linear motion and angular motion. The proposed method will be useful in such applications where only linear motions are important than angular motions or vice versa.

• 한국건설관리학회논문집
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• 제11권4호
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• pp.68-79
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• 2010

도로면 크랙실링 공법은 예방적 차원에서 도로면에 발생된 크랙을 초기에 효과적으로 보수할 수 있는 공법으로 국내외에 서는 1990년대 초반부터 기존 도로면 크랙실링 작업의 생산성, 안전성 및 품질의 균일성 확보를 목적으로 크랙실링 자동화 장비의 개발을 위한 지속적인 연구개발 노력을 수행해 왔다. 도로면 크랙실링 자동화 장비를 개발함에 있어 특히 경로계획은 주어진 작업 영역 내에서 개발 장비로 하여금 실링될 크랙 네트워크를 시간 효과적으로 횡단할 수 있도록 하는 운항 정보를 제공하게 되므로 이는 개발 장비의 성능을 결정 짖는 매우 중요한 연구주제라 할 수 있다. 본 연구의 목적은 작업 영역 내 경로계획 데이터의 효과적인 모델링을 통해 크랙실링 자동화 장비의 최적 경로계획 알고리즘을 개발하는 것으로써, 경로 집합전체를 완전 탐색하는 2단계 트리 알고리즘과 크랙의 순열만을 탐색하는 1단계 트리 알고리즘을 개발하였으며, 알고리즘의 성능 측정 및 분석을 통해 최적 경로계획 알고리즘의 적용 범위와 그에 따른 성능 향상 정도를 평가하였다. 이 연구의 결과는 도로면 크랙실링 자동화 장비의 생산성 향상에 크게 기여할 수 있을 것으로 기대된다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1136-1139
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• 1996

For on-line trajectory planning such as teleoperation it is desirable to keep good manipulability of the robot manipulators since the motion command is not given in advance. To keep good manipulability means the capability of moving any arbitrary directions of task space. An optimization process with different manipulability measures are performed and compared for a redundant robot system moving in 2-dimensional task space, and gives results that the conventional manipulability ellipsoid based on the Jacobian matrix is not good choice as far as the optimal direction of motion is concerned.

• 전자공학회논문지B
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• 제29B권11호
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• pp.36-45
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• 1992

A numerical trajectory planning method for path-constrained trajectory planning is proposed which ensures collision-free and time-optimal motions for two robotic manipulators with limited actuator torques and velocities. For each robot, physical constraints of the robots such as limited torques or limited rotational velocities of the actuators are converted to the constraints on velocity and acceleration along the path, which is described by a scalar variable denoting the traveled distance from starting point. Collision region is determined on the coordination space according to the kinematic structures and the geometry of the paths of the robots. An Extended Coordination Space is then constructed` an element of the space determines the postures and the velocities of the robots, and all the constraints described before are transformed to some constraints on the behaviour of the coordination-velocity curves in the space. A dynamic programming technique is them provided with on the discretized Extended Coordination Space to derive a collision-free and time-optimal trajectory pair. Numerical example is included.

• 산업공학
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• 제3권2호
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• pp.23-38
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• 1990

The use of robots for painting operations is a powerful alternative as a means for automation and quality improvement. A typical method being used for motion planning of the painting robot is to guide the robot along the desired path : the "lead-through" method. Although this method is simple and has been widely used, it has several drawbacks a) The robot cannot be used during the teaching period, b) A human is exposed to a hostile environment, c) The motions taught are, at best, human's skill level. To deal with the above problems, an integrated robot-trajectory planning scheme is presented. The new scheme takes CAD data describing the shape and geometry of the objects, and outputs an optimal trajectory in the sense of coating thickness and painting time. The purpose of this paper is to investigate theoretical backgrounds for such a scheme including geometric modeling, painting mechanics and robot trajectory planning, and develop algorithms for generating spray gun paths and minimum-time robot trajectories. Future study is to implement these algorithms on an workstation to develop an integrated software system ; ATPS(Automatic Trajectory Planning System) for spray painting robots.

• 한국자동차공학회논문집
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• 제22권3호
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• pp.241-249
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• 2014

This paper presents a path planning algorithm of an autonomous vehicle (ADAM III) for collision avoidance in the presence of multiple obstacles. Under the requirements that a low-cost GPS is used and its computation should be completed with a sampling time of sub-second, heading angle estimation is proposed to improve performance degradation of its measurement and a hierarchical structure for path planning is used. Once it is decided that obstacle avoidance is necessary, the path planning consists in three steps: waypoint generation, trajectory candidate generation, and trajectory selection. While the waypoints and the corresponding trajectory candidates are generated based on position of obstacles, the final desired trajectory is determined with considerations of kinematic constraints as well as an optimal condition in a term of lateral deviation. Finally the proposed algorithm was validated experimentally through field tests and its demonstration was performed in Autonomous Vehicle Competition (AVC) 2013.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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• pp.176-181
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• 2000

Collision free task planning for dual-arm robot which perform many subtasks in a common work space can be achieved in two steps : path planning and trajectory planning. path planning finds the order of tasks for each robot to minimize path lengths as well as to avoid collision with static obstacles. A trajectory planning strategy is to let each robot move along its path as fast as possible and delay one robot at its initial position or reduce speed at the middle of its path to avoid collision with the other robot.

• 제어로봇시스템학회논문지
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• 제21권5호
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• pp.471-476
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• 2015

This paper presents a maximum velocity trajectory planning algorithm for differential mobile robots with wheel velocity constraint to cope with physical limits in the joint space for two-wheeled mobile robots (TMR). In previous research, the convolution operator was able to generate a central velocity that deals with the physical constraints of a mobile robot while considering the heading angles along a smooth curve in terms of time-dependent parameter. However, the velocity could not track the predefined path. An algorithm is proposed to compensate an error that occurs between the actual and driven distance by the velocity of the center of a TMR within a sampling time. The velocity commands in Cartesian space are also converted to actuator commands to drive two wheels. In the case that the actuator commands exceed the maximum velocity the trajectory is redeveloped with the compensated center velocity. The new center velocity is obtained according to the curvature of the path to provide a maximum allowable velocity meaning a time-optimal trajectory. The effectiveness of the algorithm is shown through numerical examples.

• 한국정밀공학회지
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• 제15권3호
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• pp.157-167
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• 1998

In this paper it is purpose that reduces joint torques and their rate of change through optimizing trajectory planning of biped walking machine. The motion of biped walking machine is divided into leg motion for walking and body motion for keeping balance. The leg motion is planned by three phases, that are deploy, swing, and place phases, in terms of the state of foot against floor. The distribution of time assigned to each phase is optimized and that causes leg joint torques and their rate of change to minimize. The body notion is produced by using optimal control theory which minimizes body joint torques and satisfies Z.M.P. constraints defined as region of each phase.

• ETRI Journal
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• 제44권4호
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• pp.641-653
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• 2022

In the process of autonomous vehicle motion planning and to create comfort for vehicle occupants, factors that must be considered are the vehicle's safety features and the road's slipperiness and smoothness. In this paper, we build a mathematical model based on the combination of a genetic algorithm and a neural network to offer lane-change solutions of autonomous vehicles, focusing on human vehicle control skills. Traditional moving planning methods often use vehicle kinematic and dynamic constraints when creating lane-change trajectories for autonomous vehicles. When comparing this generated trajectory with a man-generated moving trajectory, however, there is in fact a significant difference. Therefore, to draw the optimal factors from the actual driver's lane-change operations, the solution in this paper builds the training data set for the moving planning process with lane change operation by humans with optimal elements. The simulation results are performed in a MATLAB simulation environment to demonstrate that the proposed solution operates effectively with optimal points such as operator maneuvers and improved comfort for passengers as well as creating a smooth and slippery lane-change trajectory.