• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.1898-1899
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• 2011

In this paper, we propose an obstacle avoidance algorithm for a network-based autonomous mobile robot. The obstacle avoidance algorithm is based on the VFH (Vector Field Histogram) algorithm and delay-compensative methods with the VFH algorithm are proposed for the network-based robot that is a unified system composed of distributed environmental sensors, mobile actuators, and the VFH controller. Firstly, the compensated readings of the sensors are used for building the polar histogram of the VFH algorithm. Secondly, a sensory fusion using the Kalman filter is proposed for the localization of the robot to compensate both the delay of the readings of an odometry sensor and the delay of the readings of the environmental sensors. The performance enhancements of the proposed obstacle avoidance algorithm from the viewpoint of efficient path generation and accurate goal positioning are also shown in this paper through some simulation experiments by the Marilou Robotics Studio Simulator.

• 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 Society of Naval Architects of Korea
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• v.56 no.1
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• pp.75-81
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• 2019

This study presents an automatic collision avoidance algorithm for autonomous navigation of unmanned surface vessels. The performance of the collision avoidance algorithm is heavily dependent on the estimation quality of the course and speed of traffic ships because collision avoidance maneuvers should be determined based on the predicted motions of the traffic ships and their trajectory uncertainties. In this study, the collision avoidance algorithm is implemented based on the Probabilistic Velocity Obstacle (PVO) approach considering the maritime collision regulations (COLREGs). In order to demonstrate the performance of the proposed algorithm, an extensive set of simulations was conducted and the results are discussed.

• Journal of the Society of Naval Architects of Korea
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• v.61 no.2
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• pp.106-114
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• 2024

In the 21st century, the rapid development of automation and artificial intelligence technologies is driving innovative changes in various industrial sectors. In the transportation industry, this is evident with the commercialization of autonomous vehicles. Moreover research into autonomous navigation technologies is actively underway in the aviation and maritime sectors. Consequently, for the practical implementation of autonomous ships, an effective collision avoidance algorithm has become a crucial element. Therefore, this study proposes a collision avoidance algorithm based on the Obstacle Zone by Target(OZT), which visually represents areas with a high likelihood of collisions with other ships or obstacles. The A-star algorithm was utilized to represent obstacles on a grid and assess collision risks. Subsequently, a collision avoidance algorithm was developed that performs fuzzy control based on calculated waypoints, allowing the vessel to return to its original course after avoiding the collision. Finally, the validity of the proposed algorithm was verified through collision avoidance simulations in various encounter scenarios.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.105.1-105
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• 2002

$\textbullet$ This paper deals with obstacle avoidance of a quadruped robot with a vision system and a PSD sensor. $\textbullet$ The vision system needs for obstacle recognition toward robot. $\textbullet$ Ths PSD sensor is also important element for obstacle recognition. $\textbullet$ We propose algorithm that recognizes obstacles with one vision and PSD sensor. $\textbullet$ We also propose obstacle avoidance algorithm with map from obstacle recognition algorithm. $\textbullet$ Using these algorithm, Quadruped robot can generate gait trajectory. $\textbullet$ Therefore, robot can avoid obstacls, and can move to target point.

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

• Journal of Institute of Control, Robotics and Systems
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• v.22 no.7
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• pp.552-556
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• 2016

Obstacle detection is a key feature in the safe driving control of electric wheelchairs. The suggested obstacle detection algorithm was designed to provide obstacle avoidance direction and detect the existence of cliffs. By means of this information, the wheelchair can determine where to steer and whether to stop or go. A 3D depth camera (Microsoft KINECT) is used to scan the 3D point data of the scene, extract information on obstacles, and produce a steering direction for obstacle avoidance. To be specific, ground detection is applied to extract the obstacle candidates from the scanned data and the candidates are projected onto a 2D map. The 2D map provides discretized information of the extracted obstacles to decide on the avoidance direction (left or right) of the wheelchair. As an additional function, cliff detection is developed. By defining the "cliffband," the ratio of the predefined band area and the detected area within the band area, the cliff detection algorithm can decide if a cliff is in front of the wheelchair. Vehicle tests were carried out by applying the algorithm to the electric wheelchair. Additionally, detailed functions of obstacle detection, such as providing avoidance direction and detecting the existence of cliffs, were demonstrated.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.169-178
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• 1997

This paper presents a new solution approach to moving obstacle avoidance problem of a robot. A new concept, avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function(VDF) is derived as a function of three state variables: the distance from the obstacle to the robot, outward speed of the obstacle relative to the robot, and outward speed of the robot relative to the obstacle. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terms of the VDF, an artificial potential is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived from the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid a moving obstacle in real time. Since the algorithm considers the mobility of the obstacle and robot as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 1998.03a
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• pp.88-93
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• 1998

This paper presents a new solution approach to moving obstacle avoidance problem for a mobile robot. A new concept avoidability measure(AVM) is defined to describe the state of a pair of a robot and an obstacle regarding the collision between them. As an AVM, virtual distance function(VDF) is derived as a function of the distance from the obstacle to the robot and outward speed of the obstacle relative to the robot. By keeping the virtual distance above some positive limit value, the robot avoids the obstacle. In terns of the VDF, an artificial potential field is constructed to repel the robot away from the obstacle and to attract the robot toward a goal location. At every sampling time, the artificial potential field is updated and the force driving the robot is derived form the gradient of the artificial potential field. The suggested algorithm drives the robot to avoid moving obstacles in real time. Since the algorithm considers the mobility of the obstacle as well as the distance, it is effective for moving obstacle avoidance. Some simulation studies show the effectiveness of the proposed approach.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.4
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• pp.187-194
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• 2002

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 talc motion, if there exists no obstacle, the end-effector of the robot arm moves along the predefined path. But if these exists an obstacle and close to talc 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 far collision avoidance with the obstacle. To show the feasibility of the developed algorithm, numerical simulations are carried out with changing both the positions and sites of obstacles. It was concluded that the proposed algorithm gives a good performance for obstacle avoidance.