• 제어로봇시스템학회:학술대회논문집
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• 1993.10a
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• pp.293-298
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• 1993

In this paper, methods for computing the time-optimal motion of a robotic manipulator are presented that considers the nonlinear manipulator dynamics, actuator constraints, joint limits, and obstacles. The optimization problem can be reduced to a search for the time-optimal path in the n-dimensional position space. These paths are further optimized with a local path optimization to yield a global optimal solution. Time-optimal motion of a robot with an articulated arm is presented as an example.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1402-1407
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• 2004

Moving a fragile object from an initial point to a goal location in minimum time without damage is pursued in this paper. In order to achieve the goal, first of all, the range of maximum acceleration and velocity are specified, which the manipulator can generate dynamically on the path that is planned a priori considering the geometrical constraints. Later, considering the impulsive force constraint of the object, the range of maximum acceleration and velocity are going to be obtained to keep the object safe while the manipulator is carrying it along the curved path. Finally, a time-optimal trajectory is planned within the maximum allowable range of the acceleration and velocity. This time optimal trajectory planning can be applied for real applications and is suitable for not only a continuous path but also a discrete path.

• Journal of the Korea Society of Computer and Information
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• v.22 no.2
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• pp.37-44
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• 2017

Wireless sensor networks are composed of many wireless sensor nodes that are sensing the environments. These networks have many constraints that are resource constraints, wireless communication, self-construction, etc. But they have many applications that are monitoring environment, tracking the object, etc. In this paper, a mechanism of finding QoS Satisfied multi-path is proposed in wireless sensor networks. In order to satisfy the QoS requirement, the proposed mechanism extends the AODV protocol to find multiple paths from a source node to a destination node by using the additional AODV message types that are proposed. This mechanism will be used to support many QoS applications such as minimum delay time, the better reliability and the better throughput by using the QoS satisfied multi-path. Overheads of the proposed mechanism are evaluated using simulation, and it is showed that QoS satisfied multiple paths are found with a little more overhead than the AODV mechanism.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.515-515
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• 2000

The performance of dynamic path following of a wheeled mobile robot with nonholonomic constraints has some drawbacks such as the influence of the initial state. The drawbacks can be overcome by the temporary path generator and modified output. But with the previous input-output linearization method using them, it is difficult to tune the gains, and if there are some modeling errors, the low gain can make the system unstable. And if a high gain is used to overcome the model uncertainties, the control inputs are apt to be large so the system can be unstable. In this paper. an H$_{\infty}$ controller is designed to guarantee robustness to model parameter uncertainties and to consider the magnitude of control inputs. And the solution to Hamilton Jacobi (HJ) inequality, which is essential to H$_{\infty}$ control design, is obtained by nonlinear matrix inequality (NLMI).

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.10
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• pp.3160-3172
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• 1996

A search algorithm for the collision free, time optimal transport path of overhead cranes has been proposed in this paper. The map for the working environment of overhead cranes was constructed in the form of three dimensional grid. The obstacle occupied region and unoccupied region of the map has been represented using the octree model. The best-first search method with a suitable estimation function was applied to select the knot points on the collision free transport path to the octree model. The optimization technique, minimizing the travel time required for transporting objects to the goal while subjected to the dynamic constraints of the crane system, was developed to find the smooth time optimal path in the form of cubic spline functions which interpolate the selected knot points. Several simulation results showed that the selected estimation function worked effectively insearching the knot points on the collision free transport path and that the resulting transport path was time optimal path while satisfying the dynamic constraints of the crane system.

• Industrial Engineering and Management Systems
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• v.16 no.1
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• pp.118-128
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• 2017

Uncertain factors in finical markets make the prediction of future returns and risk of asset much difficult. In this paper, a model,assuming the admissible errors on expected returns and risks of assets, assisted in the multiperiod mean variance portfolio selection problem is built. The model considers transaction costs, upper bound on borrowing risk-free asset constraints, cardinality constraints and threshold constraints. Cardinality constraints limit the number of assets to be held in an efficient portfolio. At the same time, threshold constraints limit the amount of capital to be invested in each stock and prevent very small investments in any stock. Because of these limitations, the proposed model is a mix integer dynamic optimization problem with path dependence. The forward dynamic programming method is designed to obtain the optimal portfolio strategy. Finally, to evaluate the model, our result of a meaning example is compared to the terminal wealth under different constraints.

• Journal of Aerospace System Engineering
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• v.14 no.2
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• pp.1-11
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• 2020

Detecting obstacles and generating a suitable path to avoid obstacles in real time is a prime mission requirement for UAVs. In areas, close to buildings and people, detecting obstacles in the path and estimating its own position (egomotion) in GPS degraded/denied environments are usually addressed with vision-based Simultaneous Localization and Mapping (SLAM) techniques. This presents possibilities and challenges for the feasible path generation with constraints of vehicle dynamics in the configuration space. In this paper, a near real-time feasible path is shown to be generated in the ORB-SLAM framework using a chain-based path planning approach in a force field with dynamic constraints on path length and minimum turn radius. The chain-based path plan approach generates a set of nodes which moves in a force field that permits modifications of path rapidly in real time as the reward function changes. This is different from the usual approach of generating potentials in the entire search space around UAV, instead a set of connected waypoints in a simulated chain. The popular ORB-SLAM, suited for real time approach is used for building the map of the environment and UAV position and the UAV path is then generated continuously in the shortest time to navigate to the goal position. The principal contribution are (a) Chain-based path planning approach with built in obstacle avoidance in conjunction with ORB-SLAM for the first time, (b) Generation of path with minimum overheads and (c) Implementation in near real time.

• Journal of Korean Society for Quality Management
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• v.47 no.4
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• pp.701-711
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• 2019

Purpose: The problem of optimizing redundancy allocation in multi-level systems is considered when each item in a multi-level system has alternative items with the same function. The number of redundancy of multi-level system is allocated to maximize the reliability of the system under path set and cost limitation constraints. Methods: Based on cost limitation and path set constraints, a mathematical model is established to maximize system reliability. Particle swarm optimization is employed for redundant allocation and verified by numerical experiments. Results: Comparing the particle swarm optimization method and the memetic algorithm for the 3 and 4 level systems, the particle swarm optimization method showed better performance for solution quality and search time. Particularly, the particle swarm optimization showed much less than the memetic algorithm for variation of results. Conclusion: The proposed particle swarm optimization considerably shortens the time to search for a feasible solution in MRAP with path set constraints. PS optimization is expected to reduce search time and propose the better solution for various problems related to MRAP.

• The KIPS Transactions:PartC
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• v.9C no.5
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• pp.655-664
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• 2002

The focus of quality-of-service routing has been on the routing of a single path satisfying specified QoS constraints. However upon failure of a node or link on the path, a new path (backup path) satisfying the constraints has to be established. This paper proposed the fault recovery QoS Rerouting algorithms to recovery the service of applications under fault environment of network. For this, we describes the generation method of PFC (Protection Fundamental Cycle) protecting all of network nodes and suggests path selection algorithms using minimization rerouting cost problem and analyzes the performances of these.

• International Journal of Control, Automation, and Systems
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• v.4 no.1
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• pp.10-16
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• 2006

In this paper, moving a fragile object from an initial point to a specific location in the minimum time without damage is studied. In order to achieve this goal, initially, the maximum acceleration and velocity ranges are specified. These ranges can be dynamically generate on the planned path by the manipulator. The path can be altered by considering the geometrical constraints. Later, considering the impulsive force constraint on the object, the range of maximum acceleration and velocity are obtained to preserve object safety while the manipulator is carrying it along the curved path. Finally, a time-optimal trajectory is planned within the maximum allowable range of acceleration and velocity. This time-optimal trajectory planning can be applied to real applications and is suitable for both continuous and discrete paths.