• 전기학회논문지
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• 제57권4호
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• pp.686-691
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• 2008

This paper proposes the concept of "virtual sensor data" and its application for real time obstacle avoidance. The virtual sensor data is virtual distance which takes care of the movement of the obstacle as well as that of the robot. In practical application, the virtual sensor data is calculated from the odometry data and the range sensor data. The virtual sensor data can be used in all the methods which use distance data for collision avoidance. Since the virtual sensor data considers the movement of the robot and the obstacle, the methods utilizing the virtual sensor data results in more smooth and safer collision-free motion.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 1999년도 추계학술대회논문집
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• pp.315-320
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• 1999

Obstacle Detection System(ODS) is a essential system for automated vehicle, such as AGV(Automatic Guided Vehicle), mobile robot. Automated vehicle must have a capability to detect and to avoid obstacles to guarantee a safe driving condition. To implement obstacle detection system, virtual bumper concept adapted. Like real bumper in a car, such as in the truck, it protects vehicle from collision using laser distance sensor. When an obstacle(such as other vehicle, building, etc) intrudes this virtual bumper area, a virtual force is calculated and produces necessary strategy to be able to avoid collision. In this paper, simplified virtual bumper concept is presented, and various problems when happens to implement are discussed.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.59.6-59
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• 2001

A virtual obstacle method for escaping local minima encountered by sonar-based mobile robot navigation used in real-time obstacle avoidance is presented. The new algorithm judges the mobile robot falls into local minima and helps the mobile robot escape from Et, which regards a concave obstacle as convex or flat one, virtual obstacle method. In the algorithm, it starts to make virtual-obstacle when the mobile robot meets a certain condition, then the robot mores back slowly taking inside area of local minima as obstacle gradually The new algorithm is simulated. The experimental results are presented to demonstrate the usefulness of the method.

• 한국생산제조학회지
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• 제7권1호
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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.

• 제어로봇시스템학회논문지
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• 제3권2호
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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.

• 제어로봇시스템학회논문지
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• 제13권7호
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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.

• 한국멀티미디어학회논문지
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• 제20권2호
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• pp.344-351
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• 2017

In this paper, we propose the obstacle database management module for obstacle estimation and clustering. The proposed G-eye manager system can create customized walking route for blind people using the UI manager and verify the coordinates of the path. Especially, G-eye management system designed a regional information module. The regional information module can improve the loading speed of the obstacle data by classifying the local information by clustering the coordinates of the obstacle. In this paper, we evaluate the reliability of the walking route generated from the obstacle map. We obtain the coordinate value of the path avoiding the virtual obstacle from the proposed system and analyze the error rate of the path avoiding the obstacle according to the size of the obstacle. And we analyze the correlation between obstacle size and route by classifying virtual obstacles into sizes.

• 제어로봇시스템학회논문지
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• 제16권8호
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• pp.771-779
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• 2010

This paper presents a method that integrates the geometric path tracking and the obstacle avoidance for nonholonomic mobile robot. The mobile robot follows the path by moving through the turning radius given from the pure pursuit method which is the one of the geometric path tracking methods. And the obstacle generates the obstacle potential, from this potential, the virtual force is obtained. Therefore, the turning radius for avoiding the obstacle is calculated by proportional to the virtual force. By integrating the turning radius for avoiding the obstacle and the turning radius for following the path, the mobile robot follows the path and avoids the obstacle simultaneously. The effectiveness of the proposed method is verified through the real experiments for path tracking only, static obstacle avoidance, dynamic obstacle avoidance.

• Journal of Mechanical Science and Technology
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• 제19권6호
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• pp.1290-1303
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• 2005

In this research, a remote control system has been developed and implemented, which combines autonomous obstacle avoidance in real-time with force-reflective tele-operation. A tele-operated mobile robot is controlled by a local two-degrees-of-freedom force-reflective joystick that a human operator holds while he is monitoring the screen. In the system, the force-reflective joystick transforms the relation between a mobile robot and the environment to the operator as a virtual force which is generated in the form of a new collision vector and reflected to the operator. This reflected force makes the tele-operation of a mobile robot safe from collision in an uncertain and obstacle-cluttered remote environment. A mobile robot controlled by a local operator usually takes pictures of remote environments and sends the images back to the operator over the Internet. Because of limitations of communication bandwidth and the narrow view-angles of the camera, the operator cannot observe shadow regions and curved spaces frequently. To overcome this problem, a new form of virtual force is generated along the collision vector according to both distance and approaching velocity between an obstacle and the mobile robot, which is obtained from ultrasonic sensors. This virtual force is transferred back to the two-degrees-of-freedom master joystick over the Internet to enable a human operator to feel the geometrical relation between the mobile robot and the obstacle. It is demonstrated by experiments that this haptic reflection improves the performance of a tele-operated mobile robot significantly.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 1998년도 춘계학술대회 논문집
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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.