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We combine a visual odometry system with an aided inertial navigation filter to produce a precise and robust navigation system that does not rely on external infrastructure. Incremental structure from motion with sparse bundle adjustment using a stereo camera provides real-time highly accurate pose estimates of the sensor which are combined with six degree-of-freedom inertial measurements in an Extended...
In this work we propose the use of machine learning techniques to improve Simultaneous Localization and Mapping (SLAM) using an extended Kalman filter (EKF) and visual information for robot navigation. We are using the Viola and Jones approach for looking specific visual landmarks in environment. The landmarks are used to improve the robot localization in the EKF-SLAM system. Our experiments validate...
We propose a structure and motion estimation scheme based on a dynamic systems approach, where states and parameters in a perspective system are estimated. An online method for structure and motion estimation in densely sampled image sequences is presented. The proposed method is based on an extended Kalman filter and a novel parametrization. We derive a dynamic system describing the motion of the...
A modified covariance extended Kalman filter (MVEKF) algorithm is proposed to the monocular simultaneous localization and mapping (SLAM) in this paper. Recent literatures have shown that it is possible to solve the monocular SLAM using the Extended Kalman Filter (EKF) and the inverse-depth parameterization. However, the EKF algorithm has its intrinsic disadvantage such as the divergence. Here we propose...
In this paper, a new robust approach for camera based lane recognition is presented. The tracking filter and the detection interact such that the tracking filter is used to place a region of interest for a detection of lane segments in various distances, and each successful detection is used to update the lane geometry in the tracking filter. A novel and time efficient detection algorithm is used...
Sensor based robot control allows manipulation in dynamic and uncertain environments. Vision can be used to estimate 6-DOF pose of an object by model-based pose-estimation methods, but the estimate is not accurate in all degrees of freedom. Force offers a complementary sensor modality allowing accurate measurements of local object shape when the tooltip is in contact with the object. As force and...
This paper presents a consistent framework for continuous stereo self-calibration. Based on a practical analysis of the sensitivity of stereo reconstruction to camera calibration uncertainties, we identify important parameters for self-calibration. We evaluate different geometric constraints for estimation and tracking of these parameters: bundle adjustment with reduced structure representation relating...
Sensor-based robot control allows manipulation in dynamic environments with uncertainties. Vision offers a low-cost sensor modality, but low sample rate, high sensor delay and uncertain measurements limit its usability. This paper addresses three problems: uncertain visual measurements, different sampling rates and compensation of the sensor delay. To alleviate the problems above an approach for visual...
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