• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1597-1600
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• 1997

Most autonomous mobile robots view things only in front of them. As a result they may collide against objects moving from the side or behind. To overcome the problem we have built an Active Omni-directional Range Sensor that can obtain omni-directional depth data by a laser conic plane and a conic mirror. Also we proposed a self-localization algorithm of mobile robot in unknown environment by fusion of Odometer and Active Omn-directional Range Sensor.

• Journal of Institute of Control, Robotics and Systems
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• v.12 no.7
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• pp.686-692
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• 2006

This paper shows the calculation of 3D geometric information such as height, direction and distance under the constraints of a catadioptric camera system. The catadioptric camera system satisfies the single viewpoint constraints adopting hyperboloidal mirror. To calculate the 3D information with a single omni-directional image, the points are assumed to lie in perpendicular to the ground. The infinite plane is also detected as a circle from the structure of the mirror and camera. The analytic experiments verify the correctness of theory using real images taken in indoor environments like rooms or corridors. Thus, the experimental results show the applicability to calculate the 3D geometric information using single omni-directional images.

• International Journal of Control, Automation, and Systems
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• v.5 no.2
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• pp.184-191
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• 2007

Autonomous navigation of mobile robot requires a ranging system for measurement of distance to environmental objects. It is obvious that the wider and the faster distance measurement gives a mobile robot more freedom in trajectory planning and control. The active omni-directional ranging system proposed in this paper is capable of obtaining the distance for all 3600 directions in real-time because of the omni-directional mirror and the structured light. Distance computation including the sensitivity analysis and the experiments on the omni-directional ranging are presented to verify the effectiveness of the proposed system.

• Journal of Institute of Control, Robotics and Systems
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• v.5 no.4
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• pp.437-445
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• 1999

Most autonomous mobile robots view only things in front of then, and as a result, they may collide with objects moving from the side or behind. To overcome this problem, an active omni-directional range sensor system has been built that can obtain an omni-directional depth map through the use of a laser conic plane and a conic mirror. In the navigation of the mobile robot, the proposed sensor system produces a laser conic plane by rotating the laser point source at high speed: this creates a two-dimensional depth map, in real time, once an image is captured. The results obtained from experiment show that the proposed sensor system is very efficient, and can be utilized for navigation of mobile robot in an unknown environment.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.824-827
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• 1996

Most autonomous mobile robots view things only in front of them. As a result, they may collide against objects moving from the side or behind. To overcome the problem we have built an Active Omni-directional Range Sensor that can obtain omnidirectional depth data by a laser conic plane and a conic mirror. In the navigation of the mobile robot, the proposed sensor system makes a laser conic plane by rotating the laser point source at high speed and achieves two dimensional depth map, in real time, once an image capture. The experimental results show that the proposed sensor system provides the best potential for navigation of the mobile robot in uncertain environment.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.1 s.94
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• pp.253-264
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• 1999

Most autonomous mobile robots view only things in front of them, and as a result, they may collide with objects moving from the side or behind. To overcome this problem. an Active Omni-directional Range Sensor System has been built that can obtain an omni-directional range data through the use of a laser conic plane and a conic mirror. Also, mobile robot has to know its current location and heading angle by itself as accurately as possible to successfully navigate in real environments. To achieve this capability, we propose a self-localization algorithm of a mobile robot using an active omni-directional range sensor in an unknown environment. The proposed algorithm estimates the current position and head angle of a mobile robot by a registration of the range data obtained at two positions, current and previous. To show the effectiveness of the proposed algorithm, a series of simulations was conducted and the results show that the proposed algorithm is very efficient, and can be utilized for self-localization of a mobile robot in an unknown environment.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.10 no.2
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• pp.237-242
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• 2009

Comparing with fixed-type Robots, Mobile Robots have the advantage of extending their workspaces. But this advantage need some sensors to detect mobile robot's position and find their goal point. This article describe the navigation teaching method of mobile robot using omni-directional position detection system. This system offers the brief position data to a processor with simple devices. In other words, when user points a goal point, this system revise the error by comparing its heading angle and position with the goal. For these processes, this system use a conic mirror and a single camera. As a result, this system reduce the image processing time to search the target for mobile robot navigation ordered by user.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.868-874
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• 2014

This paper proposes a novel mapping algorithm in Omni-directional Vision SLAM based on an obstacle's feature extraction using Lucas-Kanade Optical Flow motion detection and images obtained through fish-eye lenses mounted on robots. Omni-directional image sensors have distortion problems because they use a fish-eye lens or mirror, but it is possible in real time image processing for mobile robots because it measured all information around the robot at one time. In previous Omni-Directional Vision SLAM research, feature points in corrected fisheye images were used but the proposed algorithm corrected only the feature point of the obstacle. We obtained faster processing than previous systems through this process. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous $360^{\circ}$ panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we remove the feature points of the floor surface using a histogram filter, and label the candidates of the obstacle extracted. Third, we estimate the location of obstacles based on motion vectors using LKOF. Finally, it estimates the robot position using an Extended Kalman Filter based on the obstacle position obtained by LKOF and creates a map. We will confirm the reliability of the mapping algorithm using motion estimation based on fisheye images through the comparison between maps obtained using the proposed algorithm and real maps.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.2
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• pp.161-167
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• 2008

This article describes the methods of a decision of the location which user points to move by an optical device like a laser pointer and a moving to that location. Using a conic mirror and CCD camera sensor, a robot observes a spot of user wanted point among an initiative, computes the location and azimuth and moves to that position. This system offers the brief data to a processor with simple devices. In these reason, we can reduce the time of a calculation to process of images and find the target by user point for carrying a robot. User points a laser spot on a point to be moved so that this sensor system in the robot, detecting the laser spot point with a conic mirror, laid on the robot, showing a camera. The camera is attached on the robot upper body and fixed parallel to the ground and the conic mirror.

• Journal of the Korean Society for Precision Engineering
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• v.23 no.6 s.183
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• pp.22-28
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• 2006