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Uncertainty models of vision sensors in mobile robot positioning

Piotr Skrzypczyński — 2005

International Journal of Applied Mathematics and Computer Science

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...

Simultaneous Localization And Mapping: A feature-based probabilistic approach

Piotr Skrzypczyński — 2009

International Journal of Applied Mathematics and Computer Science

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...

A biologically inspired approach to feasible gait learning for a hexapod robot

Dominik BelterPiotr Skrzypczyński — 2010

International Journal of Applied Mathematics and Computer Science

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...

Efficient RGB-D data processing for feature-based self-localization of mobile robots

Marek KraftMichał NowickiRudi PenneAdam SchmidtPiotr Skrzypczyński — 2016

International Journal of Applied Mathematics and Computer Science

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...

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