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Register a new userTrajectory Servoing: Image-Based Trajectory Tracking Using SLAM
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Added by
Shiyu Feng
Publication date
2021
fields
Informatics Engineering
and research's language is
English
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This paper describes an image based visual servoing (IBVS) system for a nonholonomic robot to achieve good trajectory following without real-time robot pose information and without a known visual map of the environment. We call it trajectory servoing. The critical component is a feature-based, indirect SLAM method to provide a pool of available features with estimated depth, so that they may be propagated forward in time to generate image feature trajectories for visual servoing. Short and long distance experiments show the benefits of trajectory servoing for navigating unknown areas without absolute positioning. Trajectory servoing is shown to be more accurate than pose-based feedback when both rely on the same underlying SLAM system.
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Odometer-aided visual-inertial SLAM systems typically have a good performance for navigation of wheeled platforms, while they usually suffer from degenerate cases before the first turning. In this paper, firstly we perform an observability analysis w.r.t. the extrinsic parameters before the first turning, which is a complement of the existing results of observability analyses. Secondly, inspired by the above observability analyses, we propose a bidirectional trajectory computation method, by which the poses before the first turning are refined in the backward computation thread, and the real-time trajectory is adjusted accordingly. Experimental results prove that our proposed method not only solves the problem of the unobservability of accelerometer bias and extrinsic parameters before the first turning, but also results in more accurate trajectories in comparison with the state-of-the-art approaches.
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