Journal article

PLASCENCIA Alfredo C. and KARSTOFT Henrik. Map Building Based on a Xtion Pro Live RGBD and a Laser Sensors. Journal of Information Technology & Software Engineering. Hyderabad: OMICS Online Publishing Pvt Ltd., 2014, vol. 4, no. 1, pp. 1-7. ISSN 2165-7866. Available from: http://www.omicsgroup.org/journals/map-building-based-on-a-xtion-pro-live-rgbd-and-a-laser-sensors-2165-7866.1000126.pdf
Publication language:english
Original title:Map Building Based on a Xtion Pro Live RGBD and a Laser Sensors
Title (cs):Tvorba map založená na Xtion Pro Live RGBD a laserových senzorech
Pages:1-7
Place:IN
Year:2014
URL:http://www.omicsgroup.org/journals/map-building-based-on-a-xtion-pro-live-rgbd-and-a-laser-sensors-2165-7866.1000126.pdf
Journal:Journal of Information Technology & Software Engineering, Vol. 4, No. 1, Hyderabad, IN
ISSN:2165-7866
URL:http://www.fit.vutbr.cz/research/groups/speech/publi/2014/plascencia_it-se2014_2165-7866.1000126.pdf [PDF]
Keywords
Map Building; senzor fusion; Laser sensors; RGBD; Bayesian method
Annotation
The main contribution of this paper is to show the feasibility to use the novel Xtion Pro Live RGBD camera into the field of sensor data fusion and map making based on the well established Bayesian method. This approach involves the combination of the Xtion Pro Live RGBD camera with the Hokuyo laser sensor data readings, which are interpreted by a probabilistic heuristic model that abstracts the beam into a ray casting to an occupied grid cell. Occupancy grid is proposed for representing the probability of the occupied and empty areas. In order to update the occupancy grid, the Bayesian estimation method is applied to both sensor data arrays. The sensor data fusion yields a significant improvement of the combined occupancy grid compared to the individual occupied sensor data readings. It is also shown by the Mahalanobis distance that by integrating both sensors, more reliable and accurate maps are produced. The approach has been exemplified by following a sensor data fusion method to building a map of an indoor environment robot.
Abstract
The main contribution of this paper is to show the feasibility to use the novel Xtion Pro Live RGBD camera into the field of sensor data fusion and map making based on the well established Bayesian method. This approach involves the combination of the Xtion Pro Live RGBD camera with the Hokuyo laser sensor data readings, which are interpreted by a probabilistic heuristic model that abstracts the beam into a ray casting to an occupied grid cell. Occupancy grid is proposed for representing the probability of the occupied and empty areas. In order to update the occupancy grid, the Bayesian estimation method is applied to both sensor data arrays. The sensor data fusion yields a significant improvement of the combined occupancy grid compared to the individual occupied sensor data readings. It is also shown by the Mahalanobis distance that by integrating both sensors, more reliable and accurate maps are produced. The approach has been exemplified by following a sensor data fusion method to building a map of an indoor environment robot.
BibTeX:
@ARTICLE{
   author = {C. Alfredo Plascencia and Henrik Karstoft},
   title = {Map Building Based on a Xtion Pro Live RGBD and a Laser
	Sensors},
   pages = {1--7},
   journal = {Journal of Information Technology \& Software
	Engineering},
   volume = {4},
   number = {1},
   year = {2014},
   ISSN = {2165-7866},
   language = {english},
   url = {http://www.fit.vutbr.cz/research/view_pub.php?id=11158}
}

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