• 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.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.

• 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.1609-1614
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• 2003

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. To implement the concept in collision avoidance of 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. 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. 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.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.37.2-37
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• 2002

1. Introduction 2. Problem Formulation 3. Avoidability Measure And Relative Distance 4. Artificial Potential Field in Terms of Relative Distance 5. Simulation Results 6. Conclusions 7. Reference

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.1040-1045
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• 1991

An approach to time-varying obstacle avoidance problem is pursued. The mathematical formulation of the problem is given in Cartesian space and in joint space. To deal with the time-varying obstacles, view-time is introduced. A view-time is the time interval viewing the time-varying obstacles to model equivalent stationary obstacles. For the analysis of the properties of the view-time, avoidability measure is defined as a measure of easiness for a robot to avoid obstacles. Based on the properties, a motion planning strategy to avoid time-varying obstacles is derived. An application of the strategy to the collision-free motion planning of two SCARA robots and the simulation on the application are given.

• 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.