• The Transactions of the Korean Institute of Electrical Engineers
• /
• v.41 no.9
• /
• pp.1071-1084
• /
• 1992

In this paper, the method for navigation and obstacle avoidance of the autonomous mobile robot is proposed. The proposed algorithms are based on the fuzzy inference system which is able to deal with imprecise and uncertain information. The self-tuning algorithm, which adopts the simplex method, modifies the parameters of membership functions of the input-output linguistic variables by changing the support of these fuzzy sets according to the integral of absolute error(IAE) of the system response. The wall-follwing navigation and obstacle avoidance of the mobile robot are based on range data measured from the internal sensors(encoder) and the outer sensors(sonar sensor). In addition, the algorithm for the obstacle detection proposed in this paper is based on the expert's experience. Finally, the effectiveness of navigation and obstacle avoidance algorithm is demonstrated through simulation and experiment.

• International Journal of Aeronautical and Space Sciences
• /
• v.13 no.4
• /
• pp.474-483
• /
• 2012

In this paper, a collision avoidance maneuver was sought for low Earth orbit (LEO) and geostationary Earth orbit (GEO) satellites maintained in a keeping area. A genetic algorithm was used to obtain both the maneuver start time and the delta-V to reduce the probability of collision with uncontrolled space objects or debris. Numerical simulations demonstrated the feasibility of the proposed algorithm for both LEO satellites and GEO satellites.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1997.10a
• /
• pp.345-348
• /
• 1997

In this paper, a motion control algorithm is developed using a fuzzy control and the optimization of performance function, which makes a robot arm avoid an unexpected obstacle when the end-effector of the robot arm is moving to the goal position. During the motion, if there exists no obstacle, the end-effecter of the robot arm moves along the pre-defined path. But if there exists an obstacle and close to the robot arm, the fuzzy motion controller is activated to adjust the path of the end-effector of the robot arm. Then, the robot arm takes the optimal posture for collision avoidance with the obstacle. To show the feasibility of the developed algorithm, numerical simulations are carried out with changing both the positions and sizes of obstacles. It was concluded that the proposed algorithm gives a good performance for obstacle avoidance.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2004.04a
• /
• pp.129-134
• /
• 2004

Author presented some study with a title of "automatic control for ship collision avoidance system" in previous papers. The paper reported the tread of the study, un-sloved issues and outcome of the study. In this paper, some additional results will be reported. The first is the algorithm of avoidance of group ship that is one of the un-sloved issues. The algorithm is useful when a ship takes an avoiding action toward group fish boats and approaching group merchant vessel. The second is unified model for calculating ship collision risk. The collision risk changes with various meet type of ships. Therefor newly-developed model is suggested to take into account of these situations. Finally simulation is carried out to verify suggested algorithm and model in various ship encounter situations..

• Journal of the Institute of Convergence Signal Processing
• /
• v.3 no.2
• /
• pp.64-70
• /
• 2002

This paper proposes a new construction method of neural networks. The construction method consists of two fundmental ideas, which are a parallel selection-style evaluation and rules evolution. A new collision avoidance algorithm using genetic and neural network is proposed to avoid moving obstacles such as mobile robots. The input parameters of this algorithm is position of moving obstacles and target. Output is a regenerated direction of mobile robot. This algorithm is very simple and so, it is available to application of real time process. The pattern of collision avoidance is learned through test execution.

• IEMEK Journal of Embedded Systems and Applications
• /
• v.17 no.2
• /
• pp.115-121
• /
• 2022

This paper proposes a distributed model predictive formation control algorithm for a group of unmanned ground vehicles (UGVs) with guaranteeing collision avoidance between UGVs. Generally, the model predictive control based formation control has a disadvantage in that it takes a long time to compute control inputs when considering collision avoidance between UGVs. In this paper, in order to overcome this problem, the formation control algorithm is implemented in a distributed manner so that it could be individually controlled. Also, a collision-avoidance method considering real-time is proposed. The proposed formation control algorithm is implemented based on robot operating system (ROS), open source-based middleware. Through the various simulation tests, it is confirmed that the formation control of five UGVs is successfully performed while avoiding collisions between UGVs.

• Journal of Advanced Navigation Technology
• /
• v.26 no.6
• /
• pp.427-433
• /
• 2022

Obstacle detection, collision recognition, and avoidance technologies are required the collision avoidance technology for UAVs. In this paper, considering collinear multiple static obstacle, we propose an obstacle detection algorithm using LiDAR and a collision recognition and avoidance algorithm based on CPA. Preprocessing is performed to remove the ground from the LiDAR measurement data before obstacle detection. And we detect and classify obstacles in the preprocessed data using the K-means clustering algorithm. Also, we estimate the absolute positions of detected obstacles using relative navigation and correct the estimated positions using a low-pass filter. For collision avoidance with the detected multiple static obstacle, we use a collision recognition and avoidance algorithm based on CPA. Information of obstacles to be avoided is updated using distance between each obstacle, and collision recognition and avoidance are performed through the updated obstacles information. Finally, through obstacle location estimation, collision recognition, and collision avoidance result analysis in the Gazebo simulation environment, we verified that collision avoidance is performed successfully.

• Journal of the Korean Society for Marine Environment & Energy
• /
• v.12 no.1
• /
• pp.15-22
• /
• 2009

Auto-navigation algorithm have been studied to avoid collision and grounding of a ship due to human error. There have been many research on collision avoidance algorithms but they have been validated little on the real coastal traffic situation. In this study, a Collision Avoidance algorithm is developed by using Fuzzy algorithm and the concept of Changeable Action Space Searching (CAS). In the first step, on a basis of collision risk calculated from fuzzy algorithm in the current time(t=to), alternative Action Space for collision avoidance is planned. In the second step, next alternative Action Space for collision avoidance in the future($t=to+{\Delta}t$) is corrected and re-planned with re-evaluated collision risk. In the third step, the safest and most effective course among Action Space is selected by using optimization method in real time. In this paper, the main features of the developed collision avoidance algorithm (CAS) are introduced. CAS is implemented in the ship-handling simulator of MOERI. The performance of CAS is tested on the situation of open sea with 3 traffic ships, whose position is assumed to be informed from AIS. Own-ship is fully autonomously navigated by autopilot including the collision avoidance algorithm, CAS. Experimental results show that own-ship can successfully avoid the collision against traffic ships and the calculated courses from CAS are reasonable.

• Journal of Institute of Control, Robotics and Systems
• /
• v.17 no.8
• /
• pp.843-850
• /
• 2011

In this paper, an effective path generation algorithm for obstacle avoidance producing small amount of steering action as possible is proposed. The proposed path generation algorithm can reduce unnecessary steering because of the small lateral changes in generated waypoints when UGV (Unmanned Ground Vehicle) encounters obstacles during its waypoint navigation. To verify this, the proposed algorithm and $A^*$ algorithm are analyzed through the simulation. The proposed algorithm shows good performance in terms of lateral changes in the generated waypoint, steering changes of the vehicle while driving and execution speed of the algorithm. Especially, due to the fast execution speed of the algorithm, the obstacles that encounter suddenly in front of the vehicle within short range can be avoided. This algorithm consider the waypoint navigation only. Therefore, in certain situations, the algorithm may generate the wrong path. In this case, a general path generation algorithm like $A^*$ is used instead. However, these special cases happen very rare during the vehicle waypoint navigation, so the proposed algorithm can be applied to most of the waypoint navigation for the unmanned ground vehicle.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.7 no.8
• /
• pp.233-247
• /
• 1999

Traffic accidents are normally caused by late or faulty judgements due to the driver's inaccurate estimation of the distance, velocity, and acceleration from the surrounding vehicles as well as his carelessness or inattention. Thus, the development of collision avoidance systems is motivated by their great potential for increased vehicle safety. A typical collision avoidance system consists of the forward-looking sensor, the criteria for activation of collision warming and avoidance, the collision avoidance maneuvers, and the user interface. This thesis is concerned with the development of a collision warning algorithm in which the driver is warned of approaching collision with the visual and/or the audible signals . The warning algorithm based on fuzzy logic is presented here based on new warning criteria. It has been newly derived from the conventional warning equation by adding a new input variable of the required deceleration to avoid collision. The algorithm is also able to adapt to the individual driver's taste along with the different road conditions by externally controlling the warning intensity. Finally , the proposed algorithm has been validated using computer simulation.