• Journal of Advanced Navigation Technology
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• v.19 no.4
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• pp.288-298
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• 2015

For the commercialization of unmanned aircraft, we must validate the safety of the air/ground collision alert systems (CAS). The validation procedure of CAS requires the flight test which is not only expensive but also dangerous. To alleviate this problem, we need the simulation based validation process for the CAS. We developed an integrated UAV simulation (IUS) environment which interconnect the flight simulator, the Matlab/Simulink, and a target avionics simulation model. We developed the collision warning module of the TCAS and tested using IUS and flight encounter models. Using IUS, we can evaluate the performance and reliability of a target avionic system at the preliminary design stage of a development life cycle.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.42 no.10 s.340
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• pp.39-50
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• 2005

In this paper, we propose a performance improving MAC algerian for the IEEE 802.11 DCF. WLAN based IEEE 802.11 uses two control methods called 'Distributed Coordination Function(UF)' and 'Point Coordination Function(PCF)'. The nF controls the Urnsmission based on carrier sense multiple access with collision detection(CSMA/CA), that decides a random backoff time with the range of contention window for each terminal. Normally, each terminal the CW double after collision, and reduces the CW to the minimum after successful transmission. This paper proposes an enhanced DCF algorithm that decreases the CW smoothly after successful transmission in order to reduce the collision Probability by utilizing the current status information of WLAN. We also analyze the throughput and delay performance for the unsaturated case mathematically. Simulation results show that our algorithm enhances the saturation throughput of WLAN. They also coincide well with the analytical results.

• Journal of Digital Contents Society
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• v.9 no.1
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• pp.61-67
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• 2008

In this paper, MAC algorithm for the IEEE 802.11 DCF improving the performance is proposed and analyzed by simulation. The MAC of IEEE 802.11 WLAN to control data transmission uses two control methods called DCF(Distributed Coordination Function) and PCF(Point Coordination Function). The DCF controls the transmission based on CSMA/CA(Carrier Sense Multiple Access with Collision Avoidance), that decides a random backoff time with the range of CW(Contention Window) for each station. Normally, each station increase the CW to double after collision, and reduces the CW to the minimum after successful transmission. The DCF shows excellent performance relatively in situation that competition station is less but has a problem that performance is fallen from throughput and delay viewpoint in situation that competition station is increased. This paper proposes an enhanced DCF algorithm that increases the CW to maximal CW after collision and decreases the CW smoothly after successful transmission in order to reduce the collision probability by utilizing the current status information of WLAN. To prove efficiency of proposed algorithm, a lots of simulations are conducted and analyzed.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.4 s.181
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• pp.75-82
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• 2006

In this paper, we propose an optimal trajectory for biped robots to move up-and-down stairs using a genetic algorithm and a computed-torque control for biped robots to be dynamically stable. First, a Real-Coded Genetic Algorithm (RCGA) which of operators are composed of reproduction, crossover and mutation is used to minimize the total energy. Constraints are divided into equalities and inequalities: Equality constraints consist of a position condition at the start and end of a step period and repeatability conditions related to each joint angle and angular velocity. Inequality constraints include collision avoidance conditions of a swing leg at the face and edge of a stair, knee joint conditions with respect to the avoidance of the kinematic singularity, and the zero moment point condition with respect to the stability into the going direction. In order to approximate a gait, each joint angle trajectory is defined as a 4-th order polynomial of which coefficients are chromosomes. The effectiveness of the proposed optimal trajectory is shown in computer simulations with a 6-dof biped robot that consists of seven links in the sagittal plane. The trajectory is more efficient than that generated by the modified GCIPM. And various trajectories generated by the proposed GA method are analyzed in a viewpoint of the consumption energy: walking on even ground, ascending stairs, and descending stairs.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.64 no.10
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• pp.1479-1485
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• 2015

Robot's technology was very simple and repetitive in the past. Nowadays, robots are required to perform intelligent operation. So, path planning has been studied extensively to create a path from start position to the goal position. In this paper, potential field algorithm was used for path planning in dynamic environments. It is used for a path plan of mobile robot because it is elegant mathematical analysis and simplicity. However, there are some problems. The problems are collision risk, avoidance path, time attrition. In order to resolve path problems, we amalgamated potential field algorithm with the artificial neural network system. The input of the neural network system is set using relative velocity and location between the robot and the obstacle. The output of the neural network system is used for the weighting factor of the repulsive potential function. The potential field algorithm problem of mobile robot's path planning can be improved by using artificial neural network system. The suggested algorithm was verified by simulations in various dynamic environments.

• Journal of Internet of Things and Convergence
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• v.7 no.4
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• pp.29-34
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• 2021

In order to apply reinforcement learning to a robot in a real environment, it is necessary to use simulation in a virtual environment because numerous iterative learning is required. In addition, it is difficult to apply a learning algorithm that requires a lot of computation for a robot with low-spec. hardware. In this study, ML-Agent, a reinforcement learning frame provided by Unity, was used as a virtual simulation environment to apply reinforcement learning to the obstacle collision avoidance problem of mobile robots with low-spec hardware. A DQN supported by ML-Agent is adopted as a reinforcement learning algorithm and the results for a real robot show that the number of collisions occurred less then 2 times per minute.

• Journal of Intelligence and Information Systems
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• v.11 no.3
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• pp.25-43
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• 2005

In modern automated container terminals, automated guided vehicle (AGV) systems are considered a viable option for the horizontal tansportation of containers between the stacking yard and the quayside cranes. AGVs in a container terminal move rather freely and do not follow fixed guide paths. For an efficient operation of such AGVs, however, a sophisticated traffic management system is required. Although the flexible routing scheme allows us to find the shortest possible routes for each of the AGVs, it may incur many coincidental encounters and path intersections of the AGVs, leading to collisions or deadlocks. However, the computational cost of perfect prediction and avoidance of deadlocks is prohibitively expensive for a real time application. In this paper, we propose a traffic control method that predicts and avoids some simple, but at the same time the most frequently occurring, cases of deadlocks between two AGVs. More complicated deadlock situations are not predicted ahead of time but detected and resolved after they occur. Our method is computationally cheap and readily applicable to real time applications. The efficiency and effectiveness of our proposed methods have been validated by simulation.

• International Journal of Naval Architecture and Ocean Engineering
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• v.7 no.1
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• pp.87-99
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• 2015

In recent years, the development of autonomous surface vehicles has been a field of increasing research interest. There are two major areas in this field: control theory and path planning. This study focuses on path planning, and two objectives are discussed: path planning for Unmanned Surface Vehicles (USVs) and implementation of path planning in a real map. In this paper, satellite thermal images are converted into binary images which are used as the maps for the Finite Angle $A^*$ algorithm ($FAA^*$), an advanced $A^*$ algorithm that is used to determine safer and suboptimal paths for USVs. To plan a collision-free path, the algorithm proposed in this article considers the dimensions of surface vehicles. Furthermore, the turning ability of a surface vehicle is also considered, and a constraint condition is introduced to improve the quality of the path planning algorithm, which makes the traveled path smoother. This study also shows a path planning experiment performed on a real satellite thermal image, and the path planning results can be used by an USV.

• Journal of Drive and Control
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• v.15 no.3
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• pp.8-13
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• 2018

This paper presents a phase portrait analysis-based safety control algorithm for excavators, using adaptive sliding mode control. Since working postures and material types cause the excavator's rotational inertia to vary, the rotational inertia was estimated, and this estimation was used to design an adaptive sliding mode controller for collision avoidance of the excavator. In order to estimate the rotational inertia, the recursive least-squares estimation with multiple forgetting was applied with the information of the swing velocity of the excavator. For realistic evaluation, an actual working scenario-based performance evaluation was conducted. Based on the estimated rotational inertia and an analysis of estimation errors, sliding mode control inputs were computed. The actual working scenario-based performance evaluation of the designed safety algorithm was conducted, and the results showed that the developed safety control algorithm can efficiently avoid a collision with an object in consideration of rotational inertia variations.

• Journal of the Korean Society for Marine Environment & Energy
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• v.1 no.1
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• pp.47-55
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• 1998

In this paper, authors try to assess the marine traffic environment from the viewpoint of the degree of congestion. First, the marine traffic flow simulation is carried out to get the information related to the assessment. The simulation is performed based on the wide investigation of marine traffic environment and some statistical methods. Then the degree of congestion is reasoned by using the reasoning methods of the degree of collision risk made to develop collision avoidance system. The quantified degree of congestion reasoned by this method provides much information needed to the design and the evaluation of marine traffic environment.