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Simultaneous Localization and Mapping
2007Dieses Kapitel gibt eine Einfuhrung in die Kartenerstellung und gleichzeitige Lokalisierung mobiler Sensorplattformen. Die gemeinsame Losung dieser beiden Probleme ist eine Voraussetzung fur die Realisierung vieler technischer Systeme von leichten Fluggeraten uber autonome Roboter bis hin zu mobilen Kameras.
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Simultaneous localization and mapping with TurtleBotII
2015 16th IEEE International Symposium on Computational Intelligence and Informatics (CINTI), 2015The paper introduces a solution of Simultaneous Localization and Mapping what use basic sensors of TurtleBotlI like integrated odometer and gyroscope in Kobuki robot base, as well as XBOX 360 Kinect RGBD data. We can define new position and orientation of robot using previous location and sensors' data with Extended Kalman Filter (EKF) in indoor ...
Bence Szendy +3 more
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Simultaneous Map Building and Localization
1992This chapter attempts to combine our earlier results to develop a unified framework for navigation. Unfortunately, combining the capabilities of localization and map building described earlier is not as straightforward as one might hope; a number of complicating research issues enter the picture, which will be described below.
John J. Leonard, Hugh F. Durrant-Whyte
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Enhanced simultaneous localization and map building
2014 CACS International Automatic Control Conference (CACS 2014), 2014FastSLAM is a well-known algorithm with its purpose to process the simultaneous localization and mapping (SLAM). There are two main FastSLAM algorithms, i.e., FastSLAM 1.0 and FastSLAM 2.0. However, the speed of execution is too slow due to the superabundant comparisons of every single existing landmarks.
Tung-Yuan Lin +3 more
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Simultaneous localization and mapping (SLAM)
2009In chapter 4 the localization problem is introduced, which is the estimation of the position and orientation of the amr in its environment. It is shown that this problem can be solved with specific sensors or based on specific features of the environment.
Karsten Berns, Ewald von Puttkamer
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Simultaneous localization and sampled environment mapping
Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference, 2009Simultaneous localization and map building is a key issue to ensure the mobile robot move in an unknown environment autonomously. A hot topic of SLAM is how to build a map describing the complex environment. This paper presents a new SLAM algorithm using the sampled environment map, which describes the environment in detail, rather than represent the ...
Rongchuan Sun +3 more
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Planetary Monocular Simultaneous Localization and Mapping
Journal of Field Robotics, 2015Planetary monocular simultaneous localization and mapping (PM‐SLAM), a modular, monocular SLAM system for use in planetary exploration, is presented. The approach incorporates a biologically inspired visual saliency model (i.e., semantic feature detection) for visual perception in order to improve robustness in the challenging operating environment of ...
Bajpai, Abhinav +3 more
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Bistatic simultaneous transmitter localization and mapping
2015 Sensor Data Fusion: Trends, Solutions, Applications (SDF), 2015In a bistatic scenario, we consider the task of simultaneously estimating the positions of a non-cooperative transmitter and landmarks that reflect the transmitted signal, generating bistatic measurements at the receiver. Neither the position of the transmitter, nor the timing of transmissions are known to the receiver.
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Simultaneous Localization and Mapping in Buildings
2014Simultaneous localization and mapping (SLAM) is a family of algorithms to generate map information while positioning the moving target at the same time. SLAM algorithms rely on many elementary algorithms such as feature point tracking, loop detection, random sample consensus, surface simplification, and more.
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Multi-camera simultaneous localization and mapping
2010In this thesis, we study two aspects of simultaneous localization and mapping (SLAM) for multi-camera systems: minimal solution methods for the scaled motion of non-overlapping and partially overlapping two camera systems and enabling online, real-time mapping of large areas using the parallelism inherent in the visual simultaneous localization and ...
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