• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.79-84
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• 1992

Path planning is an important task for optimal motion of a robot in structured or unstructured environment. The goal of this paper is to plan the optimal collision-free path in 3D, when a robot is navigated to pick up some tools or to repair some parts from various locations. To accomplish the goal, the Path Coordinator is proposed to have the capabilities of an obstacle avoidance strategy and a traveling salesman problem strategy (TSP). The obstacle avoidance strategy is to plan the shortest collision-free path between each pair of n locations in 2D or in 3D. The TSP strategy is to compute a minimal system cost of a tour that is defined as a closed path navigating each location exactly once. The TSP strategy can be implemented by the Hopfield Network. The obstacle avoidance strategy in 2D can be implemented by the VGraph Algorithm. However, the VGraph Algorithm is not useful in 3D, because it can't compute the global optimality in 3D. Thus, the Path Coordinator is used to solve this problem, having the capabilities of selecting the optimal edges by the modified Genetic Algorithm and computing the optimal nodes along the optimal edges by the Recursive Compensation Algorithm.

• 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.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.52 no.4
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• pp.223-232
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• 2003

This paper presents a new method driving multiple robots to their goal position without collision. Each robot adjusts its motion based on the information on the goal location, velocity, and position of the robot and the velocity and position of the .other robots. 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 following factors: the distance from the robot to the other robots, velocity of the robot and the other robots. To implement the concept in moving robot avoidance, relative distance between the robots is derived. Our method combines the relative distance with an artificial potential field method. 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, the usual potential field method sometimes fails preventing collision or causes hasty motion, because it initiates avoidance motion later than the proposed method. The proposed method can be used to move robots in a robot soccer team to their appropriate position without collision as fast as possible.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.7 no.1
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• pp.9-21
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• 1998

This paper a new solution approach to moving obstacle avoidance problem of 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 terms 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 from 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.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2461-2466
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• 2003

This paper presents a simple sensor fusion algorithm using neural network for navigation of mobile robots with obstacle avoidance and trap recovery. The multiple sensors input sensor data to the input layer of neural network activating the input nodes. The multiple sensors used include optical encoders, ultrasonic sensors, infrared sensors, a magnetic compass sensor, and GPS sensors. The proposed sensor fusion algorithm is combined with the VFH(Vector Field Histogram) algorithm for obstacle avoidance and AGPM(Adaptive Goal Perturbation Method) which sets adaptive virtual goals to escape trap situations. The experiment results show that the proposed low-level fusion algorithm is effective for real-time navigation of mobile robot.

• 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.

• 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.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.570-575
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• 2000

This paper presents a delayed time path planning method of the Autonomous Mobile Robot using fuzzy logic controller for avoidance of obstacles in unknown environment. It is the objective of this paper to develop fuzzy control algorithms using delayed time techniques to deal with moving obstacles randomly. This control method gives the benefit of the collision free movement in real time and optimal path to the pre-settled goal. The computer simulations are demonstrated the effective of the suggested control method in obstacle avoidance.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.146-149
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• 2002

This paper presents collision avoidance for mobile robots equipped with synchro-drive using curvature trajectory by the obstacle type. he new real-time obstacle avoidance method presents how to create a curvature trajectory in which dynamics of a mobile robot is considered we controlled translation and rotational velocity of the mobile robot. Using these two speeds with curvature trajectory, the mobile robot navigates to target point without collision. We consider that the robot going to curvature trajectory by obstacle size towards a goal location. The collision avoidance has been implemented and tested using pioneer2-dxe mobile robot.

• Journal of Korean Elementary Science Education
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• v.25 no.1
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• pp.8-14
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• 2006

This study examined how pre-service elementary teachers' perceptions regarding the learning environment (learning focus/ability-meritocracy/cooperative climate) and achievement goals (mastery/performance-approach/performance-avoidance) in science education courses jointly contributed to their science teaching efficacy beliefs (personal science teaching efficacy belief/science teaching outcome expectancy). A path analysis supported a causal model in which the perception of the learning focus influenced the mastery goal, which in turn influenced the personal science teaching efficacy belief and science teaching outcome expectancy. The perception of learning focus also had a direct effect on science teaching outcome expectancy. The perception of ability-meritocracy influenced personal science teaching efficacy belief via the performance-approach (positively) or, conversely, the performance-avoidance goal (negatively). No link .was deduced from the perception of cooperative climate. The educational implications of these findings were also discussed.