An Implementation of 3D slam with planar segments

Download

index.pdf

Date

2012

Author

Turunç, Çağrı

Metadata

Show full item record

Item Usage Stats

183
views

91
downloads

Localization and mapping are vital capabilities for a mobile robot. These two capabilities strongly depend on each other and simultaneously executing both of these operations is called SLAM (Simultaneous Localization and Mapping). SLAM problem requires the environment to be represented with an abstract mapping model. It is possible to construct a map from point cloud of environment via scanner sensor systems. On the other hand, extracting higher level of features from point clouds and using these extracted features as an input for mapping system is also a possible solution for SLAM. In this work, a 4D feature based EKF SLAM system is constructed and open form of equations of algorithm are presented. The algorithm is able to use center of mass and direction of features as input parameters and executes EKF SLAM via these parameters. Performance of 4D feature based EKF SLAM was examined and compared with 3D EKF SLAM via monte-carlo simulations. By this way; it is believed that, contribution of adding a direction vector to 3D features is investigated and illustrated via graphs of monte-carlo simulations. At the second part of the work, a scanner sensor system with IR distance finder is designed and constructed. An algorithm was presented to extract planar features from data collected by sensor system. A noise model was proposed for output features of sensor and 4D EKF SLAM algorithm was executed via extracted features of scanner system. By this way, performance of 4D EKF SLAM algorithm is tested with real sensor data and output results are compared with 3D features. So in this work, contribution of using 4D features instead of 3D ones was examined via comparing performance of 3D and 4D algorithms with simulation results and real sensor data.

Subject Keywords

Mobile robots., Three-dimensional display systems., Computer algorithms., Computer vision., Artificial intelligence.

URI

http://etd.lib.metu.edu.tr/upload/12614928/index.pdf
https://hdl.handle.net/11511/22007

Collections

Graduate School of Natural and Applied Sciences, Thesis

Suggestions

OpenMETU
Core

An implementation of mono and stereo slam system utilizing efficient map management strategy Kalay, Adnan; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2008) For an autonomous mobile robot, localization and map building are vital capabilities. The localization ability provides the robot location information, so the robot can navigate in the environment. On the other hand, the robot can interact with its environment using a model of the environment (map information) which is provided by map building mechanism. These two capabilities depends on each other and simultaneous operation of them is called SLAM (Simultaneous Localization and Map Building). While various ...
A novel soft-computing technique to segment satellite images for mobile robot localization and navigation DOĞRUER, CAN ULAŞ; Koku, Ahmet Buğra; Dölen, Melik (2007-11-02) Localization of mobile robots has been studied rigorously in the last decade. A number of successful approaches such as Extended Kalman Filter, Markov Localization, and Monte Carlo Localization assume that the map of the environment is originally presented to the robot. However, an important information package like the map of the environment could not be taken for granted in most realworld problems. In this study, a novel technique composed of a combination of Fuzzy C-Means and Fuzzy Neural Network methods...
Development of a visual object localization module for mobile robots Şahin, Erol (1999-01-01) Reports preliminary results from the design and implementation of a visual object localization module for mobile robots. The module takes an object-based approach to visual processing and relies on a preprocessing step that segments objects from the image. By tracking the size and the eccentricity of the objects in the image while the robot is moving, the visual object localization module can determine the position of objects relative to the robot using the displacement obtained from its odometry. In locali...
A non-invasive speed and position sensor for induction machines using external search coils Keysan, Ozan; Ertan, Hulusi Bülent; Department of Electrical and Electronics Engineering (2009) For an autonomous mobile robot, localization and map building are vital capabilities. The localization ability provides the robot location information, so the robot can navigate in the environment. On the other hand, the robot can interact with its environment using a model of the environment (map information) which is provided by map building mechanism. These two capabilities depends on each other and simultaneous operation of them is called SLAM (Simultaneous Localization and Map Building). While various ...
Performance comparison of point and plane features for SLAM / Yörük, Mücahit; Ulusoy, İlkay; Department of Electrical and Electronics Engineering (2014) Simultaneous Localization and Mapping (SLAM) is an indispensable capability for mobile robots that explore unknown environments. This advanced method is now widely employed since the development of improvements in sensor technology, such as 3D depth cameras. To avoid the risk of the human interaction in dangerous environments, various SLAM algorithms have been developed and proposed in the literature. The aim of this study, is to develop a landmark vector that improves the SLAM performance using the planar ...

Citation Formats

Ç. Turunç, “An Implementation of 3D slam with planar segments,” M.S. - Master of Science, Middle East Technical University, 2012.