• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.12
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• pp.2498-2504
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• 2009

The fundamental research for the mobile robot navigation using the numerical optimization method is presented. We propose an image-based visual servo navigation algorithm for a wheeled mobile robot utilizing a ceiling mounted camera. For the image-based visual servoing, we define the composite image Jacobian which represents the relationship between the speed of wheels of a mobile robot and the robot's overall speed in the image plane. The rotational speed of wheels of a mobile robot can be directly related to the overall speed of a mobile robot in the image plane using the composite image Jacobian. We define the mobile robot navigation problem as an unconstrained optimization problem to minimize the cost function with the image error between the goal position and the position of a mobile robot. In order to avoid the obstacle, the modified cost function is proposed which is composed of the image error between the position of a mobile robot and the goal position and the distance between the position of a mobile robot and the position of the obstacle. The performance was evaluated using the simulation.

• The Journal of Korea Robotics Society
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• v.14 no.4
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• pp.285-292
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• 2019

Path planning is an important problem to solve in robotics and there has been many related studies so far. In the previous research, we proposed the Heterogeneous-Ants-Based Path Planner (HAB-PP) for the global path planning of mobile robots. The conventional path planners using grid map had discrete state transitions that constrain the only movement of an agent to multiples of 45 degrees. The HAB-PP provided the smoother path using the heterogeneous ants unlike the conventional path planners based on Ant Colony Optimization (ACO) algorithm. The planner, however, has the problem that the optimization of the path once found is fast but it takes a lot of time to find the first path to the goal point. Also, the HAB-PP often falls into a local optimum solution. To solve these problems, this paper proposes an improved ant-inspired path planner using the Rapidly-exploring Random Tree-star ($RRT^*$). The key ideas are to use $RRT^*$ as the characteristic of another heterogeneous ant and to share the information for the found path through the pheromone field. The comparative simulations with several scenarios verify the performance of the improved HAB-PP.

• Steel and Composite Structures
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• v.19 no.2
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• pp.349-368
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• 2015

This paper presents a new algorithm to find the optimal distribution of steel diagonal braces (SDB) using artificial bee colony optimization technique. The four different objective functions are employed based on the transfer function amplitude of; the top displacement, the top absolute acceleration, the base shear and the base moment. The stiffness parameter of SDB at each floor level is taken into account as design variables and the sum of the stiffness parameter of the SDB is accepted as an active constraint. An optimization algorithm based on the Artificial Bee Colony (ABC) algorithm is proposed to minimize the objective functions. The proposed ABC algorithm is applied to determine the optimal SDB distribution for planar buildings in order to rehabilitate existing planar steel buildings or to design new steel buildings. Three planar building models are chosen as numerical examples to demonstrate the validity of the proposed method. The optimal SDB designs are compared with a uniform SDB design that uniformly distributes the total stiffness across the structure. The results of the analysis clearly show that each optimal SDB placement, which is determined based on different performance objectives, performs well for its own design aim.

• Advances in materials Research
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• v.13 no.1
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• pp.1-18
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• 2024

The present experimental investigation focuses on finding optimal parametric data-set of laser micro-drilling operation with minimum taper and Heat-affected zone during laser micro-drilling of Carbon Nanotube/Epoxy-based composite materials. Experiments have been conducted as per Box-Behnken design (BBD) techniques considering cutting speed, lamp current, pulse frequency and air pressure as input process parameters. Then, the relationship between control parameters and output responses is developed using second-order nonlinear regression models. The analysis of variance test has also been performed to check the adequacy of the developed mathematical model. Using the Response Surface Methodology (RSM) and an Accelerated particle swarm optimization (APSO) technique, optimum process parameters are evaluated and compared. Moreover, confirmation tests are conducted with the optimal parameter settings obtained from RSM and APSO and improvement in performance parameter is noticed in each case. The optimal process parameter setting obtained from predictive RSM based APSO techniques are speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), Air pressure (1 kg/cm²) for Taper and speed=150 (m/s), current=22 (amp), pulse frequency (3 kHz), air pressure (3 kg/cm²) for HAZ. From the confirmatory experimental result, it is observed that the APSO metaheuristic algorithm performs efficiently for optimizing the responses during laser micro-drilling process of nanocomposites both in individual and multi-objective optimization.

• International conference on construction engineering and project management
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• 2024.07a
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• pp.242-246
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• 2024

Automated route planning is an important tool in the field of built environment. For example, a high-quality route planning method can improve the logistics planning of projects, thereby enhancing the performance of projects and the effectiveness of management. However, the traditional automated route planning is performed based on the predicted mean value travel time of candidate routes. Such a point estimate neglects the purpose of the trip and can further lead to a suboptimal decision. Motivated by this challenge, this study proposes an innovative framework for trip purpose based route planning. The proposed artificial intelligence and stochastic optimization framework recommends the most appropriate travel route for decision makers by fully considering their trip requirements beyond just the shortest mean value travel time. In addition to its theoretical contributions, our proposed route planning method will also contribute to the current logistics planning practice. Future research may be devoted to the real-life implementation of the proposed methodology in a broader context to provide empirical insights for practitioners in various industries.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.4
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• pp.403-413
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• 1990

A collision free trajectory control for multiple mobile robots in obstacle-resident workspace is proposed. The proposed method is based on the concept of neural optimization network which has been applied to such problems which are too complex to be handled by traditional analytical methods, and gives good adaptibility for unpredictable environment. In this paper, the positions of the mobile robot are taken as the variables of the neural circuit and the differential equations are derived based on the performance index which is the weighted summation of the functions of the distances between the goal and current position of each robot, between each pair of robots and between the goal and current position of each robot, between each pair of robots and between obstacles and robots. Also is studied the problem of local minimum and of detour in large radius around obstacles, which is caused by inertia of mobile robots. To show the validity of the proposed method an example is illustrated by computer simulation, in which 6 mobile robots with mass and friction traverse in a workspace with 6 obstacles.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.683-686
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• 2000

A new approach to the task of aligning a robot using camera is presented in this paper. We apply an elitist GA to find the joints angles of manipulator to reach target position instead of using nonlinear least error method. Since it employs parallel search and have good performance in solving optimization problems. In order to improve convergence speed, the floating coding method and geometry constraint conditions are used. Experiments are carried out to exhibit the effectiveness of vision-based control using elitist genetic algorithm.

• Journal of the Korea Institute of Military Science and Technology
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• v.12 no.1
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• pp.18-23
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• 2009

It is hard to find an operation case using anti-submarine searching pattern(ASSP) developed by Korean navy since Korean navy has begun submarine searching operation. This paper proposes the method to develop hull mount sonar(HMS) based optimal submarine searching pattern by using genetic algorithm. Developing the efficient ASSP based on theory in near sea environment has been demanded for a long time. Submarine searching operation can be executed by using ma ulti-step and multi-layed method. however, In this paper, we propose only HMS based ASSP generation method considering the ocean environment and submarine searching tactics as a step of first research. The genetic algorithm, known as a global opination method, optimizes the parameters affecting efficiency of submarine searching operation. Finally, we confirm the performance of the proposed ASSP by simulation.

• Phonetics and Speech Sciences
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• v.2 no.4
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• pp.137-143
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• 2010

In this paper, a speech endpoint detection algorithm is proposed. The proposed algorithm is a kind of state transition-based ones for speech detection. To reject short-duration acoustic pulses which can be considered noises, it utilizes duration information of all detected pulses. For the optimization of parameters related with pulse lengths and energy threshold to detect speech intervals, an exhaustive search scheme is adopted while speech recognition rates are used as its performance index. Experimental results show that the proposed algorithm outperforms the baseline state-based endpoint detection algorithm. At 5 dB input SNR for the beamforming input, the word recognition accuracies of its outputs were 78.5% for human voice noises and 81.1% for music noises.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.12
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• pp.581-588
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• 2000

This paper presents the power system application of a PWM base UPFC through EMTP simulation. A PWM base UPFC model is constructed and detailed switching-level simulation is performed using EMTP. The dynamic responses of UPFC are analyzed. Based on the simulation results, the appropriate equivalent impedances of UPFC voltage-source model which represent similar dynamics with PWM based UPFC are determined by optimization routine. This paper also analyzes the influence of the power system strength on the dynamic responses of UPFC. Finally this paper shows that the performance of UPFC is improved by control parameter tuning when UPFC is installed to weak power system.