MAP BUILDING FOR CLUTTERED ENVIRONMENT
Published In: INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTER AND INFORMATION TECHNOLOGY
Author(s): ARASH TOUDESHKI , ABD RAHMAN RAMLI , HABIBU RABIU , M. HAMIRUCE MARHABAN , SITI A AHMAD , YUNUSA ALI S
Abstract: This paper presents a novel approach to scene localization and mapping in indoor environments from the concept of the Image Bag of Words (BOW) technique, where a group of native feature descriptors represents images and are subsequently transformed to a separate set of image words. This approach uses the famed algorithm called Scale invariant Feature Transform (SIFT). To extract distinctive invariant feature for reliable matching, we normalized the images as illumination changes affect the feature extraction. To achieve robust and efficient matching the environment is modelled. Clustering is shown to be appropriate for quantizing these descriptors into clusters based on selected threshold. In this work, we developed an efficient SLAM using images captured from a highly cluttered background. The result indicates a promising trend in using the camera for SLAM implementation.
- Publication Date: 05-May-2013
- DOI: 10.15224/978-981-07-6261-2-27
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THE BOUNDARY ITERATIVE-DEEPENING DEPTH-FIRST SEARCH ALGORITHM
Published In: INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTER AND INFORMATION TECHNOLOGY
Author(s): ANG LI-MINN , K.P. SENG , L.S. YEONG , LIM KAI L , S. I. CH’NG
Abstract: Boundary searches were introduced in pathfinding aiming to find a middle-ground between memory intensive algorithms such as the A* search algorithm and the cycle redundancy of iterative-deepening algorithms such as the IDA*. Boundary search algorithms allocate a small memory footprint during runtime to store frontier nodes between each iteration to reduce redundancy, while expanding nodes in the same manner as iterative-deepening algorithms. The boundary search algorithm fringe search is an informed search algorithm derived from the IDA* for use in known environments. This paper proposes the boundary iterative-deepening depth-first search (BIDDFS) algorithm, which fills the gap made by the fringe search for uninformed search algorithms. The BIDDFS is optimised to perform blind searches in unknown environments, where simulation experiments found that it is up to more than 3 times faster than standard uninformed iterative-deepening algorithms.
- Publication Date: 05-May-2013
- DOI: 10.15224/978-981-07-6261-2-26
- Views: 0
- Downloads: 0