• Transactions of the Korean Society of Automotive Engineers
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• v.18 no.3
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• pp.116-126
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• 2010

The Korean rolling stock safety regulation stipulates that the collision deceleration of a car body should be maintained under average 5g and maximum 7.5g during train collisions. One-dimensional dynamic model of a full rake train, which is made up of nonlinear springs/bars-dampers-masses, is often used to estimate the collision decelerations of car bodies in a basic design stage. By the way, the previous studies have often used some average force-deformation curve for energy absorbing structures in rolling stock. Through this study, we intended to analyse how much the collision deceleration levels are influenced by the initial peak force modeling in the one-dimensional force-deformation curve. The numerical results of the one-dimensional dynamic model for the Korean High-Speed Train show that the initial peak force modeling gives significant effect on the collision deceleration levels. Therefore the peak force modeling of the force-deformation curve should be considered in one-dimensional dynamic model of a full rake train to evaluate the article 16 of the domestic rolling stock safety regulations.

• The Journal of Korea Robotics Society
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• v.17 no.1
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• pp.32-39
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• 2022

Since the mobile platform and the manipulator mounted on it move at the same time in a mobile manipulator, the risk of mutual collision increases. Most of the studies on collision avoidance of mobile manipulators cannot be applied to differential drive type mobile platforms or the end-effector tends to deviate from the desired trajectory for collision avoidance. In this study, a collision avoidance algorithm based on null space projection (CANS) that solves these two problems is proposed. To this end, a modified repulsive force that overcomes the non-holonomic constraints of a mobile platform is generated by adding a virtual repulsive force in the direction of its instantaneous velocity. And by converting this repulsive force into a repulsive velocity and applying it to the null space, the end-effector of the robot avoids a collision while moving along its original trajectory. The proposed CANS algorithm showed excellent performance through self-collision avoidance tests and door opening tests.

• Journal of Mechanical Science and Technology
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• v.18 no.1
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• pp.132-144
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• 2004

This paper presents a new method driving multiple robots to their goal position without collision. To consider the movement of the robots in a work area, we adopt the concept of avoidability measure. The avoidability measure figures the degree of how easily a robot can avoid other robots considering the velocity of the robots. To implement the concept to avoid collision among multiple robots, relative distance between the robots is proposed. The relative distance is a virtual distance between robots indicating the threat of collision between the robots. Based on the relative distance, the method calculates repulsive force against a robot from the other robots. Also, attractive force toward the goal position is calculated in terms of the relative distance. These repulsive force and attractive force are added to form the driving force for robot motion. The proposed method is simulated for several cases. The results show that the proposed method steers robots to open space anticipating the approach of other robots. In contrast, since the usual potential field method initiates avoidance motion later than the proposed method, it sometimes fails preventing collision or causes hasty motion to avoid other robots. The proposed method works as a local collision-free motion coordination method in conjunction with higher level of task planning and path planning method for multiple robots to do a collaborative job.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.9
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• pp.799-808
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• 2004

In this paper, a new collision avoidance algorithm based on the dynamic model of a mobile robot is proposed. In order to avoid obstacles on the path of a mobile robot, intelligent force control is used to regulate accurate distance between a robot and an obstacle. Since uncertainties from robot and environment dynamics degrade the performance of a collision avoidance task, neural network is used to compensate for uncertainties so that the collision avoidance can be performed intelligently. Simulation studies are conducted to confirm the proposed collision avoidance tracking control algorithm.

• Journal of KSNVE
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• v.10 no.3
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• pp.474-479
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• 2000

Piston slap is not only one of the major sources of noise and vibration in internal combustion engines but also a cause of the deterioration of engine performance. The basic mechanism associated with the piston slap seems to be quite simple but the phenomenon is in fact complicated with regard to many mechanical elements associated, First of all the impact force of piston slap must be identified to estimate engine block surface vibration, In this paper model of collision point is proposed to calculate the impact force when slap surface vibration. In this paper model of collision point is proposed to calculate the impact force when slap occurs. The parameters of the model are estimated by employing the concept of point mobility, . The predicted and experimentally observed vibration results confirm that the proposed method is practically useful.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2007.12a
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• pp.376-382
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• 2007

A Collapse of bridge by ship's collision to the bridge post may lead a great calamity. This paper investigates on avoiding collision between a ship and bridge by improvement of environmental factors, submitting a counter plan of reducing collision effect by triangular type of collision protecting bar and ship maneuvering skills. Putting up collision protecting bar fences of triangular type around the bridge posts would decrease the collision impact force by 75 percent.

• Journal of Mechanical Science and Technology
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• v.19 no.6
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• pp.1290-1303
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• 2005

In this research, a remote control system has been developed and implemented, which combines autonomous obstacle avoidance in real-time with force-reflective tele-operation. A tele-operated mobile robot is controlled by a local two-degrees-of-freedom force-reflective joystick that a human operator holds while he is monitoring the screen. In the system, the force-reflective joystick transforms the relation between a mobile robot and the environment to the operator as a virtual force which is generated in the form of a new collision vector and reflected to the operator. This reflected force makes the tele-operation of a mobile robot safe from collision in an uncertain and obstacle-cluttered remote environment. A mobile robot controlled by a local operator usually takes pictures of remote environments and sends the images back to the operator over the Internet. Because of limitations of communication bandwidth and the narrow view-angles of the camera, the operator cannot observe shadow regions and curved spaces frequently. To overcome this problem, a new form of virtual force is generated along the collision vector according to both distance and approaching velocity between an obstacle and the mobile robot, which is obtained from ultrasonic sensors. This virtual force is transferred back to the two-degrees-of-freedom master joystick over the Internet to enable a human operator to feel the geometrical relation between the mobile robot and the obstacle. It is demonstrated by experiments that this haptic reflection improves the performance of a tele-operated mobile robot significantly.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.631-636
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• 2007

An efficient obstacle avoidance algorithm is proposed in this paper to avoid dynamic obstacles using a collision vector while a tele-operated mobile robot is moving. For the verification of the algorithm, an operator watches through a monitor and controls the mobile robot with a force-reflection joystick. The force-reflection joystick transmits a virtual force to the operator through the Inter-net, which is generated by an adaptive impedance algorithm. To keep the mobile robot safe from collisions in an uncertain environment, the adaptive impedance algorithm generates the virtual force which changes the command of the operator by pushing the operator's hand to a direction to avoid the obstacle. In the conventional virtual force algorithm, the avoidance of moving obstacles was not solved since the operator cannot recognize the environment realistically by the limited communication bandwidth and the narrow view-angle of the camera. To achieve the dynamic obstacle avoidance, the adaptive virtual force algorithm is proposed based on the collision vector that is a normal vector from the obstacle to the mobile robot. To verify the effectiveness of the proposed algorithm, mobile robot navigation experiments with multiple moving obstacles have been performed, and the results are demonstrated.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.26 no.2
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• pp.47-53
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• 2018

In this paper, we investigate a collision avoidance algorithm for unmanned aerial vehicles using potential field based on the relative velocity of obstacles. The potential field consists of the attraction force and the repulsive force that are generated for the target and the obstacles. And the field can be classified into the attractive potential field generated by the target and the repulsive potential field generated by the obstacle, respectively. In this study, we construct an attractive potential field as a function of the distance between the UAV and the target position. On the other hand, a repulsive potential field is created by a function of distance and the relative velocity of the obstacle with respect to the UAV. The proposed potential field based collision avoidance algorithm is evaluate through simulations.

• Journal of the Korean Society of Marine Environment & Safety
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• v.28 no.1
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• pp.175-183
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• 2022

The collision between a ship and bridge across a waterway may result in extremely serious consequences that may endanger the safety of life and property. Therefore, factors affecting ship bridge collision must be investigated, and the impact force should be discussed based on various collision conditions. In this study, a finite element model of ship bridge collision is established, and the peak impact force of a ship bridge collision based on 50 operating conditions combined with three input parameters, i.e., ship loading condition, ship speed, and ship bridge collision angle, is calculated via numerical simulation. Using neural network models trained with the numerical simulation results, the prediction model of the peak impact force of ship bridge collision involving an extremely short calculation time on the order of milliseconds is established. The neural network models used in this study are the basic backpropagation neural network model and Elman neural network model, which can manage temporal information. The accuracy of the neural network models is verified using 10 test samples based on the operating conditions. Results of a verification test show that the Elman neural network model performs better than the backpropagation neural network model, with a mean relative error of 4.566% and relative errors of less than 5% in 8 among 10 test cases. The trained neural network can yield a reliable ship bridge collision force instantaneously only when the required parameters are specified and a nonlinear finite element solution process is not required. The proposed model can be used to predict whether a catastrophic collision will occur during ship navigation, and thus hence the safety of crew operating the ship.