• International Journal of Control, Automation, and Systems
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• v.1 no.1
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• pp.68-75
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• 2003

This paper presents an effective trajectory planning algorithm for industrial robot manipulators. Given the end-effector trajectory in Cartesian space, together with the relevant constraints and task specifications, the proposed method is capable of planning the optimum end-effector trajectory. The proposed trajectory planning algorithm considers the joint acceleration limit, end-effector velocity limits, and trajectory allowance. A feedforward compensator is also incorporated in the proposed algorithm to counteract the delay in joint dynamics. The algorithm is carefully designed so that it can be directly adopted with the existing industrial manipulators. The proposed algorithm can be easily programmed for various tasks given the specifications and constraints. A three-dimensional test trajectory was planned with the proposed algorithm and tested with the Performer MK3s industrial manipulator. The results verified effective manipulator performance within the constraints.

• Journal of the Korean Society of Industry Convergence
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• v.19 no.1
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• pp.18-30
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• 2016

In this paper, we propose a new technique to the design and real-time control of an adaptive controller for robotic manipulator based on digital signal processors. The Texas Instruments DSPs(TMS320C80) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved Lyapunov second method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for a dual arm robot manipulator with eight joints. joint space and cartesian space.

• Transactions of the Korean Society of Mechanical Engineers
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• v.17 no.2
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• pp.267-276
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• 1993

This paper discusses the neural network application in the study on the obstacle avoidance of robot manipulator during the trajectory planning. The collision problem of two robot manipulators which are simultaneously moving in the same workspace is investigated. Instead of the traditional modeling method, this paper processing based on the calculation of joint angle in the cartesian coordinate with constrained condition shows the possibility of real time control. The problem of the falling into the local minima is cleared by the adaptive weight factor control using the temperature adding method. Computer simulations are shown for the verification.

• Journal of Mechanical Science and Technology
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• v.18 no.1
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• pp.92-105
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• 2004

A new algorithm for planning a collision-free path based on algebraic curve is developed and the concept of collision-free Path Space (PS) is introduced. This paper presents a Geometry Mapping (GM) based on two straight curves in which the intermediate connection point is organized in elliptic locus ($\delta$, $\theta$). The GM produces two-dimensional PS that is used to create the shortest collision-free path. The elliptic locus of intermediate connection point has a special property in that the total distance between the focus points through a point on ellipse is the same regardless of the location of the intermediate connection point on the ellipse. Since the radial distance, a, represents the total length of the path, the collision-free path can be found as the GM proceeds from $\delta$=0 (the direct path) to $\delta$=$\delta$$\_$max/(the longest path) resulting in the minimum time search. The GM of elliptic workspace (EWS) requires calculation of interference in circumferential direction only. The procedure for GM includes categorization of obstacles to .educe necessary calculation. A GM based on rectangular workspace (RWS) using Cartesian coordinate is also considered to show yet another possible GM. The transformations of PS among Circular Workspace Geometry Mapping (CWS GM) , Elliptic Workspace Geometry Mapping (EWS GM) , and Rectangular Workspace Geometry Mapping (RWS GM), are also considered. The simulations for the EWS GM on various computer systems are carried out to measure performance of algorithm and the results are presented.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.576-583
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• 2000

A robust position control using a sliding mode controller is adopted for the stable dynamic walking of the biped. For the biped robot that is modeled with 14 degrees of freedom rigid bodies using the method of the multibody dynamics, the joint angles for simulation are obtained by the velocity transformation matrix using the given Cartesian foot and trunk trajectories. Hertz force model and Hysteresis damping element which is used in explanation of the energy dissipation during contact with ground are used for modeling of the ground reactions during the simulation. By the obtained that forces which contains highly confused noise elements and the system modeling uncertainties of various kinds such as unmodeled dynamics and parameter inaccuracies, the biped system will be unstable. For that problems, we are adopting a nonlinear robust control using a sliding mode controller. Under the assumption that the esimation error on the unknown parameters is bounded by a given function, that controller provides a successful way to preserve stability and achieve good performance, despite the presence of strong modeling imprecisions or uncertainties.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.12
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• pp.1220-1230
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• 2006

In this paper, we propose a flew technique to the design and real-time control of an adaptive controller for robotic manipulator based on digital signal processors. The Texas Instruments DSPs(TMS320C80) chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved Lyapunov second method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for a dual arm robot manipulator with eight joints. joint space and cartesian space.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1993.10a
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• pp.850-858
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• 1993

Germinatin and early growth of tobacco seedlings in trays containing many cells is increasing in popularity . Since 100 % germination is not likely , a major problem is to locate and replace the content of those cells which contain either no seedling or a stunted seedling with a plug containing a viable seedling. Empty cells and seedlings of poor quality take up valuable space in a greenhouse. They may also cause difficulty when transplanting seedlings into the field. Robotic technology, including the implementation of computer vision, appears to be an attractive alternative to the use of manual labor for accomplishing this task. Operating AGBOT, short for Agricultural ROBOT, involved four steps : (1) capturing the image, (2) processing the image, (3) moving the manipulator, (4) working the gripper. This research seedlings within a cell-grown environment. the configuration of the cell-grown seedling environment dictated the design of a Cartesian robot suitable for working ov r a flat plane. Experiments of AGBOT performance in transferring large seedlings produced trays which were more than 98% survived one week after transfer. In general , the system generated much better than expected.

• Journal of Biosystems Engineering
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• v.26 no.2
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• pp.163-168
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• 2001

A manipulator for test-cup attachment modules, which was a part of a robot milking system, was developed to reduce cost and labor for cow milking processing. A Cartesian coordinate manipulator was designed for the milking process, because it was quite flexible and can be constructed more economically than any other configuration. The manipulator was made use of DC motors, screws for power transmission, a RS422 interface system for the transmission of coordinate values and a one-chip microprocessor, 89C52. Performance tests of the manipulator were conducted to measure experimentally the precision of all axes. Some of the results are as follows. 1. The Cartesian coordinate manipulator was designed and built. Dimension of the three perpendicular axes (X, Y, and Z) and one arm’s axis(W) to pick up and transfer the modules were 700㎜$\times$450㎜$\times$550㎜$\times$650㎜. The arm’s axis moved the teat-cup attachment module, which attached four teat-cup to four teats, detached four teat-cup from four teats, was designed and manufactured by using CAD, CAM and CNC. 3. After 10 replications of exercising the manipulator, mean precision values(positioning error) of X, Y, Z axes wee 0.48㎜, 0.20㎜, 0.19㎜, respectively. Therefore, we conclude the axes to have a precision better than 0.5㎜, had no problem to operate correctly the milking manipulator.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.42 no.5 s.305
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• pp.1-12
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• 2005

A Mobile manipulator - a serial connection of a mobile robot and a task robot - is a very useful system to achieve various tasks in dangerous environment. because it has the higher performance than a fixed base manipulator in regard to the size of it's operational workspace. Unfortunately the use of a mobile robot introduces non-holonomic constraints, and the combination of a mobile robot and a manipulator generally introduces kinematic redundancy. In this paper, first a method for estimating the position of object at the cartesian coordinate system acquired by using the geometrical relationship between the image captured by 2-DOF active camera mounted on mobile robot and real object is proposed. Second, we propose a method to determine a optimal path between current the position of mobile manipulator whose mobile robot is non-holonomic and the position of object estimated by image information through the global displacement of the system in a symbolic way, using homogenous matrices. Then, we compute the corresponding joint parameters to make the desired displacement coincide with the computed symbolic displacement and object is captured through the control of a manipulator. The effectiveness of proposed method is demonstrated by the simulation and real experiment using the mobile manipulator.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.3
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• pp.139-149
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• 2015

In this paper, we describe a new approach to perform real-time implementation of an robust controller for robotic manipulator based on digital signal processors in this paper. The Texas Instruments DSPs chips are used in implementing real-time adaptive control algorithms to provide enhanced motion control performance for dual-arm robotic manipulators. In the proposed scheme, adaptation laws are derived from model reference adaptive control principle based on the improved direct Lyapunov method. The proposed adaptive controller consists of an adaptive feed-forward and feedback controller and time-varying auxiliary controller elements. The proposed control scheme is simple in structure, fast in computation, and suitable for real-time control. Moreover, this scheme does not require any accurate dynamic modeling, nor values of manipulator parameters and payload. Performance of the proposed adaptive controller is illustrated by simulation and experimental results for robot manipulator consisting of dual arm with eight degrees of freedom at the joint space and cartesian space.