Use of Optical Flow Information with three Cameras for Robot Navigation

Lee, Soo-Yong

doi:10.5302/j.icros.2012.18.2.110

Journal of Institute of Control, Robotics and Systems

2012

DOI: 10.5302/j.icros.2012.18.2.110

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Use of Optical Flow Information with three Cameras for Robot Navigation

Soo-Yong Lee¹

Abstract: This paper describes a new design of optical flow estimation system with three cameras. Optical flow provides useful information of camera movement; however a unique solution is not usually available for unknowns including the depth information. A camera and two tilted cameras are used to have different view of angle and direction of movement to the camera axis. Geometric analysis is performed for cases of several independent movements. The ideas of taking advantage of the extra information for robot navigatio… Show more

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Cited by 3 publications

References 11 publications

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Multi-robot Formation based on Object Tracking Method using Fisheye Images

Choi¹,

Kim²,

Choi³

et al. 2013

Journal of Institute of Control, Robotics and Systems

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This paper proposes a novel formation algorithm of identical robots based on object tracking method using omnidirectional images obtained through fisheye lenses which are mounted on the robots. Conventional formation methods of multirobots often use stereo vision system or vision system with reflector instead of general purpose camera which has small angle of view to enlarge view angle of camera. In addition, to make up the lack of image information on the environment, robots share the information on their positions through communication. The proposed system estimates the region of robots using SURF in fisheye images that have 360°of image information without merging images. The whole system controls formation of robots based on moving directions and velocities of robots which can be obtained by applying Lucas-Kanade Optical Flow Estimation for the estimated region of robots. We confirmed the reliability of the proposed formation control strategy for multi-robots through both simulation and experiment.

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Multi-robot Formation based on Object Tracking Method using Fisheye Images

Choi¹,

Kim²,

Choi³

et al. 2013

Journal of Institute of Control, Robotics and Systems

View full text Add to dashboard Cite

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Localization using Ego Motion based on Fisheye Warping Image

Choi¹,

Choi²,

Choi³

et al. 2014

Journal of Institute of Control, Robotics and Systems

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This paper proposes a novel localization algorithm based on ego-motion which used Lucas-Kanade Optical Flow and warping image obtained through fish-eye lenses mounted on the robots. The omnidirectional image sensor is a desirable sensor for real-time view-based recognition of a robot because the all information around the robot can be obtained simultaneously. The preprocessing (distortion correction, image merge, etc.) of the omnidirectional image which obtained by camera using reflect in mirror or by connection of multiple camera images is essential because it is difficult to obtain information from the original image. The core of the proposed algorithm may be summarized as follows: First, we capture instantaneous 360° panoramic images around a robot through fish-eye lenses which are mounted in the bottom direction. Second, we extract motion vectors using Lucas-Kanade Optical Flow in preprocessed image. Third, we estimate the robot position and angle using ego-motion method which used direction of vector and vanishing point obtained by RANSAC. We confirmed the reliability of localization algorithm using ego-motion based on fisheye warping image through comparison between results (position and angle) of the experiment obtained using the proposed algorithm and results of the experiment measured from Global Vision Localization System.

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Omni-directional Vision SLAM using a Motion Estimation Method based on Fisheye Image

Choi¹,

Choi²,

Dai³

et al. 2014

Journal of Institute of Control, Robotics and Systems

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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° 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.

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Use of Optical Flow Information with three Cameras for Robot Navigation

Cited by 3 publications

References 11 publications

Multi-robot Formation based on Object Tracking Method using Fisheye Images

Multi-robot Formation based on Object Tracking Method using Fisheye Images

Localization using Ego Motion based on Fisheye Warping Image

Omni-directional Vision SLAM using a Motion Estimation Method based on Fisheye Image

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