EKF Based Pose Estimation using Two Back-to-Back Stereo Pairs

Ragab, Mohammad Ehab; Wong, Kin Hong; Chen, J.Z.; Chang, Ming

doi:10.1109/icip.2007.4379540

Cited by 7 publications

(4 citation statements)

References 15 publications

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“…Comparing to the vertical stereo pair, we have noticed that the horizontal stereo pair has estimates for (t y , α, and γ) generally closer to zero (as it should be). The reasons for this are embedded in equations (2), and (3). In equation (2), a term of the camera coordinates for camera 3 is a matrixby-vector multiplication (R j D 3 ).…”

Section: Discussionmentioning

confidence: 99%

“…In fact, the EKF is a suitable real-time estimator especially when the motion pattern is not of a chaotic nature (such as robot motion limited by motor capabilities and robot mass). To estimate robot pose, two back-to-back stereo pairs are used in [2], and the approach is studied further in [3] by comparing with subsets of cameras having different constructions of the EKF. Four non-overlapping cameras are motivated in [4] by the readiness for parallel processing deployment.…”

Section: Introductionmentioning

confidence: 99%

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Robot Pose Estimation: A Vertical Stereo Pair Versus a Horizontal One

Ragab¹,

Wong²

2015

IJCSIT

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In this paper, we study the effect of the layout of multiple cameras placed on top of an autonomous mobile robot. The idea is to study the effect of camera layout on the accuracy of estimated pose parameters. Particularly, we compare the performance of a vertical-stereo-pair put on the robot at the axis of rotation to that of a horizontal-stereo-pair. The motivation behind this comparison is that the robot rotation causes only a change of orientation to the cameras on the axis of rotation. On the other hand, off-axis cameras encounter additional translation beside the change of orientation. In this work, we show that for a stereo pair encountering sequences of large rotations, at least a reference camera should be put on the axis of rotation. Otherwise, the obtained translations have to be corrected based on the location of the rotation axis. This finding will help robot designers to develop vision systems that are capable of obtaining accurate pose for navigation control. An extensive set of simulations and real experiments have been carried out to investigate the performance of the studied camera layouts encountering different motion patterns. As the problem at hand is a real-time application, the extended Kalman filter (EKF) is used as a recursive estimator.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Robot Pose Estimation: A Vertical Stereo Pair Versus a Horizontal One

Ragab¹,

Wong²

2015

IJCSIT

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“…Additionally, a single camera, one EKF for pose, and many EKFs for structure are used in [10]. Moreover, four cameras arranged in two back-to-back stereo pairs, and one EKF for pose are used in [11] while the structure is obtained on-demand using triangulation. On the other hand, two cameras arranged as a one stereo pair, and one EKF for pose are used in [12] without solving for structure.…”

Section: Introductionmentioning

confidence: 99%

A Parallel Implementation of Multiple Non-overlapping Cameras for Robot Pose Estimation

2014

KSII TIIS

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Image processing and computer vision algorithms are gaining larger concern in a variety of application areas such as robotics and man-machine interaction. Vision allows the development of flexible, intelligent, and less intrusive approaches than most of the other sensor systems. In this work, we determine the location and orientation of a mobile robot which is crucial for performing its tasks. In order to be able to operate in real time there is a need to speed up different vision routines. Therefore, we present and evaluate a method for introducing parallelism into the multiple non-overlapping camera pose estimation algorithm proposed in [1]. In this algorithm the problem has been solved in real time using multiple non-overlapping cameras and the Extended Kalman Filter (EKF). Four cameras arranged in two back-to-back pairs are put on the platform of a moving robot. An important benefit of using multiple cameras for robot pose estimation is the capability of resolving vision uncertainties such as the bas-relief ambiguity. The proposed method is based on algorithmic skeletons for low, medium and high levels of parallelization. The analysis shows that the use of a multiprocessor system enhances the system performance by about 87%. In addition, the proposed design is scalable, which is necaccery in this application where the number of features changes repeatedly.

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“…Once this rigidity constraint is estimated, minimal pose problems [18] are solved to locate the multi-camera system [3,9,12,13,23], with an Extended Kalman Filter [11,21] or with a structure from motion algorithm [23,24,25]. Some of these articles claim to use a manual extrinsic calibration.…”

Section: Introductionmentioning

confidence: 99%

Calibration of Non-Overlapping Cameras---Application to Vision-Based Robotics

Lébraly¹,

Royer²,

Ait-Aider³

et al. 2010

Procedings of the British Machine Vision Conference 2010

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Multi-camera systems are more and more used in vision-based robotics. An accurate extrinsic calibration is usually required. In most of cases, this task is done by matching features through different views of the same scene. However, if the cameras fields of view do not overlap, such a matching procedure is not feasible anymore.This article deals with a simple and flexible extrinsic calibration method, for nonoverlapping camera rig. The aim is the calibration of non-overlapping cameras embedded on a vehicle, for visual navigation purpose in urban environment. The cameras do not see the same area at the same time. The calibration procedure consists in manoeuvring the vehicle while each camera observes a static scene. The main contributions are a study of the singular motions and a specific bundle adjustment which both reconstructs the scene and calibrates the cameras. Solutions to handle the singular configurations, such as planar motions, are exposed. The proposed approach has been validated with synthetic and real data.

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EKF Based Pose Estimation using Two Back-to-Back Stereo Pairs

Cited by 7 publications

References 15 publications

Robot Pose Estimation: A Vertical Stereo Pair Versus a Horizontal One

Robot Pose Estimation: A Vertical Stereo Pair Versus a Horizontal One

A Parallel Implementation of Multiple Non-overlapping Cameras for Robot Pose Estimation

Calibration of Non-Overlapping Cameras---Application to Vision-Based Robotics

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