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Uncertainty models of vision sensors in mobile robot positioning

100%
Skrzypczyński P.
International Journal of Applied Mathematics and Computer Science
|
2005
|
tom 15
|
nr 1
73-88
EN
This paper discusses how uncertainty models of vision-based positioning sensors can be used to support the planning and optimization of positioning actions for mobile robots. Two sensor types are considered: a global vision with overhead cameras, and an on-board camera observing artificial landmarks. The developed sensor models are applied to optimize robot positioning actions in a distributed system of mobile robots and monitoring sensors, and to plan the sequence of actions for a robot cooperating with the external infrastructure supporting its navigation.
2
Content available remote

Simultaneous Localization And Mapping: A feature-based probabilistic approach

100%
Skrzypczyński P.
International Journal of Applied Mathematics and Computer Science
|
2009
|
tom 19
|
nr 4
575-588
EN
This article provides an introduction to Simultaneous Localization And Mapping (SLAM), with the focus on probabilistic SLAM utilizing a feature-based description of the environment. A probabilistic formulation of the SLAM problem is introduced, and a solution based on the Extended Kalman Filter (EKF-SLAM) is shown. Important issues of convergence, consistency, observability, data association and scaling in EKF-SLAM are discussed from both theoretical and practical points of view. Major extensions to the basic EKF-SLAM method and some recent advances in SLAM are also presented.
3
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A biologically inspired approach to feasible gait learning for a hexapod robot

64%
Belter D., Skrzypczyński P.
International Journal of Applied Mathematics and Computer Science
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2010
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tom 20
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nr 1
69-84
EN
The objective of this paper is to develop feasible gait patterns that could be used to control a real hexapod walking robot. These gaits should enable the fastest movement that is possible with the given robot's mechanics and drives on a flat terrain. Biological inspirations are commonly used in the design of walking robots and their control algorithms. However, legged robots differ significantly from their biological counterparts. Hence we believe that gait patterns should be learned using the robot or its simulation model rather than copied from insect behaviour. However, as we have found tahula rasa learning ineffective in this case due to the large and complicated search space, we adopt a different strategy: in a series of simulations we show how a progressive reduction of the permissible search space for the leg movements leads to the evolution of effective gait patterns. This strategy enables the evolutionary algorithm to discover proper leg co-ordination rules for a hexapod robot, using only simple dependencies between the states of the legs and a simple fitness function. The dependencies used are inspired by typical insect behaviour, although we show that all the introduced rules emerge also naturally in the evolved gait patterns. Finally, the gaits evolved in simulations are shown to be effective in experiments on a real walking robot.
4
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Efficient RGB-D data processing for feature-based self-localization of mobile robots

45%
Kraft M., Nowicki M., Penne R., Schmidt A., Skrzypczyński P.
International Journal of Applied Mathematics and Computer Science
|
2016
|
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.
5
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Control aspects of the blackboard agent architecture for a mobile robot

45%
Brzykcy G., Martinek J., Meissner A., Skrzypczyński P.
Control and Cybernetics
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2003
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tom 32
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nr 4
851-866
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