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Tracking an omnidirectional evader with a differential drive robot at a bounded variable distance

100%
Ruiz U., Marroquin J., Murrieta-Cid R.
International Journal of Applied Mathematics and Computer Science
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2014
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tom 24
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nr 2
371-385
EN
In this paper, we address the pursuit-evasion problem of tracking an Omnidirectional Agent (OA) at a bounded variable distance using a Differential Drive Robot (DDR), in an Euclidean plane without obstacles. We assume that both players have bounded speeds, and that the DDR is faster than the evader, but due to its nonholonomic constraints it cannot change its motion direction instantaneously. Only a purely kinematic problem is considered, and any effect due to dynamic constraints (e.g., acceleration bounds) is neglected. We provide a criterion for partitioning the configuration space of the problem into two regions, so that in one of them the DDR is able to control the system, in the sense that, by applying a specific strategy (also provided), the DDR can achieve any inter-agent distance (within an error bound), regardless of the actions taken by the OA. Particular applications of these results include the capture of the OA by the DDR and maintaining surveillance of the OA at a bounded variable distance.
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Efficient RGB-D data processing for feature-based self-localization of mobile robots

88%
Kraft M., Nowicki M., Penne R., Schmidt A., Skrzypczyński P.
International Journal of Applied Mathematics and Computer Science
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2016
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tom 26
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nr 1
63-79
EN
The problem of position and orientation estimation for an active vision sensor that moves with respect to the full six degrees of freedom is considered. The proposed approach is based on point features extracted from RGB-D data. This work focuses on efficient point feature extraction algorithms and on methods for the management of a set of features in a single RGB-D data frame. While the fast, RGB-D-based visual odometry system described in this paper builds upon our previous results as to the general architecture, the important novel elements introduced here are aimed at improving the precision and robustness of the motion estimate computed from the matching point features of two RGB-D frames. Moreover, we demonstrate that the visual odometry system can serve as the front-end for a pose-based simultaneous localization and mapping solution. The proposed solutions are tested on publicly available data sets to ensure that the results are scientifically verifiable. The experimental results demonstrate gains due to the improved feature extraction and management mechanisms, whereas the performance of the whole navigation system compares favorably to results known from the literature.
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Fuzzy logic gain scheduling for non-linear servo tracking

75%
Brdyś M. A., Littler J. J.
International Journal of Applied Mathematics and Computer Science
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2002
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tom 12
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nr 2
209-219
EN
This paper proposes the use of gain scheduling as a method of controlling a servo system with hard non-linear elements. The servo controls two elements of a tracker mounted on a ship at sea. There is stiction at the zero velocity point and non-linear friction against the motion of each tracker axis. A dual feedback loop control structure is employed. Fuzzy logic is used to provide smoothly varying non-linear scheduling functions to map the velocity of the servo relevant to the deck of the ship onto the rate loop controller parameters. Consideration is given to the use of a derivative signal as a secondary input to the fuzzy inference system. Results are presented which demonstrate that this method of controlling the servo system gives a dramatic improvement over the traditional linear control methodology for low velocity tracking performance. A linear PID controller is used in the outer loop and its design is also given some consideration.
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