• 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.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.4
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• pp.824-831
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• 2009

This paper proposes an obstacle avoidance algorithm for an autonomous mobile robot. The proposed method based on the circular navigation with probability distribution finds local-paths to avoid collisions. Futhermore, it makes mobile robots to achieve obstacle avoidance and optimal path planning due to the accurate decision of the final goal. Simulation results are included to show the feasibility of the proposed method.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.7
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• pp.883-888
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• 2004

In this paper, we propose a method to avoid obstacles that have unstable limit cycles in a chaos trajectory surface. We assume all obstacles in the chaos trajectory surface have a Van der Pol equation with an unstable limit cycle. When a chaos UAVs meet an obstacle in an Arnold equation, Chua's equation and hyper-chaos equation trajectory the obstacle reflects the UAV( Unmanned Aerial Vehicle).

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.691-694
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• 2000

In this paper, a motion control algorithm is proposed by using neural network system, which makes a robot arm successfully avoid unexpected obstacle when the robot is moving from the start to the goal position. During the motion, if there is an obstacle the vision system recognizes it. And in every time the optimization-algorithm quickly chooses a motion among the possible motions of robot. The proposed algorithm has a good avoidance characteristic in simulation.

• 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 Institute of Control, Robotics and Systems
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• v.15 no.4
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• pp.385-389
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• 2009

This paper deals with the enhancement of the complex potential navigation for wheeled mobile robots. The circle theorem from complex function theory is used to avoid an obstacle, and the enhancement to avoid multiple obstacles is proposed. The limit cycle navigation can be combined for robot to kick the ball to the intentioned direction. Avoiding step and superposing twin vortices can be applied to adjust the direction of robot's trajectory. The proposed method is verified through a set of simulation works, and the feasibilities for the enhancement of complex potential theory are successful.

• Journal of Institute of Control, Robotics and Systems
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• v.15 no.11
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• pp.1102-1107
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• 2009

An ultrasonic sensor has been widely used as a range sensor for its low cost and capability of detecting some obstacles, such as glasses and black surfaces, which are not well detected by a laser scanner and an IR sensor. Although low-cost sensors are preferred for practical service robots, they suffer from the inaccurate and insufficient range information. This paper proposes a novel approach to obstacle avoidance using low-cost anisotropic ultrasonic sensors with wide beam angle. In this paper, obstacles can be detected by the proposed sensor configuration which consists of one transmitter and three receivers. Because even wide obstacles are represented by a point, which corresponds to the intersection of range data from each receiver of the anisotropic sensor, a robot cannot avoid wide obstacles successfully. This paper exploits the probabilistic mapping technique to avoid collision with various types of obstacles. The experimental results show that the proposed method can robustly avoid obstacles in most indoor environments.

• Journal of Institute of Control, Robotics and Systems
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• v.18 no.12
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• pp.1132-1138
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• 2012

The MPC (Model Predictive Control) is one of the techniques that can be used to control an unmanned vehicle. It predicts the future vehicle trajectory using the dynamic characteristic of the vehicle and generate the control value to track the reference path. If some obstacles are detected on the reference paths, the MPC can generate control value to avoid the obstacles imposing the inequality constraints on the MPC cost function. In this paper, we propose an obstacle modeling algorithm for MPC with inequality constraints for obstacle avoidance and a method to set selective constraint on the MPC for stable obstacle avoidance. Simulations with the field test data show successful obstacle avoidance and way point tracking performance.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.325-326
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• 2010

• 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.