• 제목/요약/키워드: motion optimization

검색결과 542건 처리시간 0.029초

Repetitive Periodic Motion Planning and Directional Drag Optimization of Underwater Articulated Robotic Arms

  • Jun Bong-Huan;Lee Jihong;Lee Pan-Mook
    • International Journal of Control, Automation, and Systems
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    • 제4권1호
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    • pp.42-52
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    • 2006
  • In order to utilize hydrodynamic drag force on articulated robots moving in an underwater environment, an optimum motion planning procedure is proposed. The drag force acting on cylindrical underwater arms is modeled and a directional drag measure is defined as a quantitative measure of reaction force in a specific direction in a workspace. A repetitive trajectory planning method is formulated from the general point-to-point trajectory planning method. In order to globally optimize the parameters of repetitive trajectories under inequality constraints, a 2-level optimization scheme is proposed, which adopts the genetic algorithm (GA) as the 1st level optimization and sequential quadratic programming (SQP) as the 2nd level optimization. To verify the validity of the proposed method, optimization examples of periodic motion planning with the simple two-link planner robot are also presented in this paper.

신경망 최적화 회로를 이용한 여유자유도 로봇의 유연 가조작 모션 제어 방법 (A Dexterous Motion Control Method of Redundant Robot Manipulators based on Neural Optimization Networks)

  • Hyun, Woong-Keun;Jung, Young-Kee
    • 한국정보통신학회논문지
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    • 제5권4호
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    • pp.756-765
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    • 2001
  • An effective dexterous motion control method of redundant robot manipulators based on neural optimization network is proposed to satisfy multi-criteria such as singularity avoidance, minimizing energy consumption, and avoiding physical limits of actuator, while performing a given task. The method employs a neural optimization network with parallel processing capability, where only a simple geometric analysis for resolved motion of each joint is required instead of computing of the Jacobian and its pseudo inverse matrix. For dexterous motion, a joint geometric manipulability measure(JGMM) is proposed. JGMM evaluates a contribution of each joint differential motion in enlarging the length of the shortest axis among principal axes of the manipulability ellipsoid volume approximately obtained by a geometric analysis. Redundant robot manipulators is then controlled by neural optimization networks in such a way that 1) linear combination of the resolved motion by each joint differential motion should be equal to the desired velocity, 2) physical limits of joints are not violated, and 3) weighted sum of the square of each differential joint motion is minimized where weightings are adjusted by JGMM. To show the validity of the proposed method, several numerical examples are illustrated.

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구속조건을 고려한 캐릭터의 움직임 변경 (The Motion Transformation of Character Included Contrained Optimization Problem)

  • 이지홍;이원희;조인성
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2002년도 하계종합학술대회 논문집(3)
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    • pp.223-226
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    • 2002
  • If one can easily modify the existing motion data to a new motion in making an animation movie, he can save a lot of time for graphic design. To implement this kind of system, we propose a PC-based system composed of low cost commercial animation tool (3D Studio Max) for visualization of the animation and motion editing module that handles optimization process during the motion transform. Researchers studying advanced motion transform techniques only have to focus on the mathematical manipulation of the motion data

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수명적, 계산적 최적화를 위한 희소코드모션 알고리즘 (A Sparse Code Motion Algorithm forlifetime and computational optimization)

  • 심손권
    • 한국컴퓨터산업학회논문지
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    • 제5권9호
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    • pp.1079-1088
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    • 2004
  • 일반적으로 코드 모션 알고리즘은 계산적 최적화와 레지스터 과부하와 연관되는 실행시간 최적화를 수행 한다. 본 논문은 계산적 최적화와 수명적 최적화에 더하여 코드의 크기를 고려하는 희소 코드 모션 알고리즘을 제안한다. 희소 코드 모션 알고리즘에서 BCM 알고리즘은 계산적으로 최적 코드 모션을 수행하고, LCM 알고리즘은 레지스터 과부하를 감소시킨다. 희소 코드 모션 알고리즘은 블필요한 코드 모션을 억제시키기 때문에 계산적으로나 수명적으로 최적인 알고리즘이다. 희소 코드 모션 알고리즘은 성능평가를 통하여 기존의 연구보다 프로그램의 능률 및 실행시간을 향상시켰다.

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효율적인 애니메이션을 위한 모션 에디팅 방법의 계산량분석에 관한 연구 (Analysis on the Computational complexities of Motion Editing for Graphic Animation)

  • 이지홍;김인식;김성수
    • 제어로봇시스템학회논문지
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    • 제8권1호
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    • pp.28-36
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    • 2002
  • Regarding efficient development of computer graphic animations, lots of techniques for editing or transforming existing motion data have been developed. Basically, the motion transformation techniques follow optimization process. To make the animation be natural, almost all the techniques utilize kinematics and dynamics in constructing constraints for the optimization. Since the kinematic and dynamic structures of virtual characters to be animated are very complex, the most time-consuming part is known to the optimization process. In order to suggest some guide lines to engineers involved in the motion transformation, in this paper, we analyze the computational complexities for typical motion transformation in quantitative manner as well as the possibility for parallel computation.

An Evolutionary Optimization Approach for Optimal Hopping of Humanoid Robots

  • Hong, Young-Dae
    • Journal of Electrical Engineering and Technology
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    • 제10권6호
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    • pp.2420-2426
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    • 2015
  • This paper proposes an evolutionary optimization approach for optimal hopping of humanoid robots. In the proposed approach, the hopping trajectory is generated by a central pattern generator (CPG). The CPG is one of the biologically inspired approaches, and it generates rhythmic signals by using neural oscillators. During the hopping motion, the disturbance caused by the ground reaction forces is compensated for by utilizing the sensory feedback in the CPG. Posture control is essential for a stable hopping motion. A posture controller is utilized to maintain the balance of the humanoid robot while hopping. In addition, a compliance controller using a virtual spring-damper model is applied for stable landing. For optimal hopping, the optimization of the hopping motion is formulated as a minimization problem with equality constraints. To solve this problem, two-phase evolutionary programming is employed. The proposed approach is verified through computer simulations using a simulated model of the small-sized humanoid robot platform DARwIn-OP.

인체모션 데이터 획득 장치와 최적화 기법을 사용한 로봇운동 데이터 생성과 애니메이션 (Generation and Animation of Optimal Robot Joint Motion data using Captured Human Motion data)

  • 배태영;김영석
    • 한국생산제조학회지
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    • 제22권3_1spc호
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    • pp.558-565
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    • 2013
  • This paper describes a whole-body (human body's) motion generation scheme for an android robot that uses motion capture device and a nonlinear constrained optimization method. Because the captured motion data are based on global coordinates and the actors have different heights and different upper-lower body ratios, the captured motion data cannot be used directly for a humanoid robot. In this paper, we suggest a method for obtaining robot joint angles, which allow the resultant robot motion to be as close as possible to the captured human motion data, by applying a nonlinear constrained optimization method. In addition, the results are animated to demonstrate the similarity of the motions.

장애물이 있는 환경하에서 여유자유도 로보트의 지능제어 방법 (Intelligent Control of Redundant Manipulator in an Environment with Obstacles)

  • 현웅근;서일홍
    • 대한전기학회논문지
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    • 제41권5호
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    • pp.551-561
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    • 1992
  • A neural optimization network and fuzzy rules are proposed to control the redundant robot manipulators in an environment with obstacle. A neural optimization network is employed to solve the optimization problem for resolved motion control of redundant robot manipulators in an environment with obstacle. The fuzzy rules are proposed to determine the weights of neural optimization networks to avoid the collision between robot manipulators and obstacle. The inputs of fuzzy rules are the resultant distance and change of the distance and sum of the changes by differential motion of each joint. And the output of fuzzy rules is defined as the capability of collision avoidance of joint differential motion. The weightings of neural optimization networks are adjusted according to the capability of collision aboidance of each joint. To show the validities of the proposed method, computer simulation results are illustrated for the redundant robot of the planar type with three degrees of freedom.

신경망 최적화 회로에 의한 여유자유도를 갖는 로보트의 제어 (Redundant Robot Control by Neural Optimization Networks)

  • 현웅근;서일홍
    • 대한전기학회논문지
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    • 제39권6호
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    • pp.638-648
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    • 1990
  • An effective resolved motion control method of redundant manipulators is proposed to minimize the energy consumption and to increase the dexterity while satisfying the physical actuator constraints. The method employs the neural optimization networks, where the computation of Jacobian matrix is not required. Specifically, end effector movement resulting from each joint differential motion is first separated into orthogonal and tangential components with respect to a given desired trajectory. Then the resolved motion is obtained by neural optimization networks in such a way that 1) linear combination of the orthogonal components should be null 2) linear combination of the tangential components should be the differential length of the desired trajectory, 3) differential joint motion limit is not violated, and 4) weighted sum of the square of each differential joint motion is minimized. Here the weighting factors are controlled by a newly defined joint dexterity measure as the ratio of the tangential and orthogonal components.

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Synthesis of four-bar linkage motion generation using optimization algorithms

  • Phukaokaew, Wisanu;Sleesongsom, Suwin;Panagant, Natee;Bureerat, Sujin
    • Advances in Computational Design
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    • 제4권3호
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    • pp.197-210
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    • 2019
  • Motion generation of a four-bar linkage is a type of mechanism synthesis that has a wide range of applications such as a pick-and-place operation in manufacturing. In this research, the use of meta-heuristics for motion generation of a four-bar linkage is demonstrated. Three problems of motion generation were posed as a constrained optimization probably using the weighted sum technique to handle two types of tracking errors. A simple penalty function technique was used to deal with design constraints while three meta-heuristics including differential evolution (DE), self-adaptive differential evolution (JADE) and teaching learning based optimization (TLBO) were employed to solve the problems. Comparative results and the effect of the constraint handling technique are illustrated and discussed.