• 대한기계학회논문집A
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• 제24권4호
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• pp.848-857
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• 2000

A pick-and-place operation in 3-dimensional environment is basic operation for human and multi-purpose manipulators. However, there may be a difficult problem for such manipulators. Especially, if the object cannot be moved with a single grasp, regrasping, which can be a time-consuming process, should be carried out. Regrasping, given initial and final pose of the target object, is a construction of sequential transition of object poses that are compatible with two poses in the point of grasp configuration. This paper presents a novel approach for solving regrasp problem. The approach consists of a preprocessing and a planning stage. Preprocessing, which is done only once for a given robot, generates a look-up table which has information of kinematically feasible task space of end-effector through all the workspace. Then, using the table planning automatically determines possible intermediate location, pose and regrasp sequence leading from the pick-up to put-down grasp. Experiments show that the presented is complete in the total workspace. The regrasp planner was combined with existing path.

• 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.

• 한국해양공학회지
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• 제36권1호
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• pp.41-49
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• 2022

With the advancement of intelligent vehicles and unmanned systems, there is a growing interest in underwater surveys using autonomous marine vehicles (AMVs). This study presents an automated planning strategy for a long-term survey mission using a fleet of AMVs consisting of autonomous surface vehicles and autonomous underwater vehicles. Due to the complex nature of the mission, the actions of the vehicle must be of high-level abstraction, which means that the actions indicate not only motion of the vehicle but also symbols and semantics, such as those corresponding to deploy, charge, and survey. For automated planning, the planning domain definition language (PDDL) was employed to construct a mission planner for realizing a powerful and flexible planning system. Despite being able to handle abstract actions, such high-level planners have difficulty in efficiently optimizing numerical objectives such as obtaining the shortest route given multiple destinations. To alleviate this issue, a widely known technique in operations research was additionally employed, which limited the solution space so that the high-level planner could devise efficient plans. For a comprehensive evaluation of the proposed method, various PDDL-based planners with different parameter settings were implemented, and their performances were compared through simulation. The simulation result shows that the proposed method outperformed the baseline solutions by yielding plans that completed the missions more quickly, thereby demonstrating the efficacy of the proposed methodology.

• 대한기계학회논문집A
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• 제29권2호
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• pp.176-187
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• 2005

This paper presents an evaluation of joint configurations of a robotic finger based on kinematic analysis. The evaluation is based on an assumption that the current control methods for the fingers require that the contact state specified by the motion planner be maintained during manipulation. Various finger-joint configurations have been evaluated for different contact motions. In the kinematic analysis, the surface of the manipulated object was represented by B-spline surface and the surface of the finger was represented by cylinders and a half ellipsoid. Three types of contact motion, namely, 1) pure rolling, 2) twist-roiling, and 3) slide-twist-rolling are assumed in this analysis. The finger-joint configuration best suited for manipulative motion is determined by the dimension of manipulation workspace. The evaluation has shown that the human-like fingers are suitable for maintaining twist-rolling and slide-twist-rolling but not for pure rolling. A finger with roll joint at its fingertip link, which is different from human fingers, proved to be better for pure rolling motion because it can accommodate sideway motions of the object. Several kinds of useful finger-joint configurations suited for manipulating objects by fingertip surface are proposed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1992년도 한국자동제어학술회의논문집(국내학술편); KOEX, Seoul; 19-21 Oct. 1992
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• pp.387-392
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• 1992

This paper presents a local trajectory generation method which is based on a sequence of reference posture-velocities and the efficient low level control algorithm which constructs the complete smooth curve from the trajectory specification. The reference trajectory generator(RTG) which is in between the local path planner(LPP) and the robot motion controller(RMC) generates a sequence of set-points for each path segments from the LPP and pass it to the RMC. The RMC controls the motions of vehicle which should follow the sequence. In the feedback controller of VMC, the method which compensates robot posture-velocity error correctly is used. These methods are implemented on indoor autonomous vehicle, 'ALIVE' mobile robot. The ALIVE mobile robot system is implemented on the 32bit VME bus system: the two VME CPU's are used for RTG and RMC, while the 80C196KC-based VME board is used for motor controller.

• 제어로봇시스템학회논문지
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• 제17권5호
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• pp.429-435
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• 2011

This paper presents a sensor fusion-based estimation of heading and a Bezier curve-based motion planning for unmanned ground vehicle. For the vehicle to drive itself autonomously and safely, it should estimate its pose with sufficient accuracy in reasonable processing time. The vehicle should also have a path planning algorithm that enables to adapt to various situations on the road, especially at intersections. First, we address a sensor fusion-based estimation of the heading of the vehicle. Based on extended Kalman filter, the algorithm estimates the heading using the GPS, IMU, and wheel encoders considering the reliability of each sensor measurement. Then, we propose a Bezier curve-based path planner that creates several number of path candidates which are described as Bezier curves with adaptive control points, and selects the best path among them that has the maximum probability of passing through waypoints or arriving at target points. Experiments under various outdoor conditions including at intersections, verify the reliability of our algorithm.

• Transactions on Control, Automation and Systems Engineering
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• 제2권1호
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• pp.62-68
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• 2000

Fixtures are used in almost all phases of machining and assembly to position and hold a part accurately. The class of fixture which consists of 3 locators and 1 clamp(3L/1C) is known as the minimal set that can provide form closure which is a kinematic constraint condition for preventing all planar motions. This type of fixtures has advantages in terms of the number of fixture elements required, the time for clamping, and so on. However it is not widely used in industry because reliable loading scheme has not been reported. In this paper, we propose a method to load the class of 3L/1C fixtures using compliant motions. The planner is developed for synthesizing compliant motions to achieve precise final fixture configuration in the presence of sensing and control uncertainties. A novel approach to eliminate uncertainty in part orientation by adding one extra fixture element called an aligning pin is proposed.

• 대한기계학회:학술대회논문집
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• 대한기계학회 2007년도 춘계학술대회A
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• pp.1161-1166
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• 2007

This paper proposes the Elastic Force application on the obstacle avoidance of the Silvermate Robot. The method deals with the problem associated with the Silvermate robot driving to a goal configuration as avoiding obstacles. The initial trajectory of a robot is determined by a motion planner, and the trajectory modification is accomplished by adjusting the control points. The control points are obtained based on the elastic force approach. Consequently the trajectory of a robot is incrementally modified to maintain a smooth and adaptive trajectory in an environment with obstacles. The suggested algorithm drivers the robot to obstacle avoid in real-time. Finally, the simulation studies are carried out to illustrate the effectiveness of the proposed approach

• 제어로봇시스템학회논문지
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• 제10권9호
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• pp.755-762
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• 2004

In this research, EOG(Electrooculogram) signal was analyzed to predict the subject's intention using a fuzzy classifier. The fuzzy classifier is built automatically using the EOG data and evolutionary algorithms. An assistant robot manipulator in redundant configuration has been developed, which operates according to the EOG signal classification results. For automatic fuzzy model construction without any experts' knowledge, an evolutionary algorithm with the new representation scheme, design of adequate fitness function and evolutionary operators, is proposed. The proposed evolutionary algorithm can optimize the number of fuzzy rules, the number of fuzzy membership functions, parameter values for the each membership functions, and parameter values for the consequent parts. It is shown that the fuzzy classifier built by the proposed algorithm can classify the EOG data efficiently. Intelligent motion planner that consists of several neural networks are used for control of robot manipulator based upon EOG classification results.

• 한국공작기계학회논문집
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• 제16권5호
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• pp.33-40
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• 2007

This paper proposes the Elastic force application on the obstacle avoidance of Silvermate robots. The method deals with the problem associated with a Silvermate robot driving to a goal configuration as avoiding obstacles. The initial trajectory of a robot is determined by a motion planner, and the trajectory modification is accomplished by adjusting the control points. The control points are obtained based on the elastic force approach. Consequently the trajectory of a robot is incrementally modified to maintain a smooth and adaptive trajectory in an environment with obstacles. The suggested algorithm drives the robot to avoid obstacle in real-time. Finally, The simulation studies are carried out to illustrate the effectiveness of the proposed approach.