1A1-E15 Three dimensional map building by scan matching with two laser range sensors

2009 ◽  
Vol 2009 (0) ◽  
pp. _1A1-E15_1-_1A1-E15_3
Author(s):  
Yuji MIYAUCHI ◽  
Takashi Ogino ◽  
Toshinari Akimoto ◽  
Akihiro Matsumoto
Keyword(s):  
Three Dimensional ◽  
Map Building ◽  
Scan Matching ◽  
Laser Range ◽  
Range Sensors

Development of a laser range finder for three-dimensional map building in rubble

2005 ◽  
Vol 19 (3) ◽  
pp. 273-294 ◽  
Author(s):  
Masamitsu Kurisu ◽  
Yasuyoshi Yokokohji ◽  
Yusuke Shiokawa ◽  
Takayuki Samejima
Keyword(s):  
Three Dimensional ◽  
Laser Range Finder ◽  
Map Building ◽  
Range Finder ◽  
Laser Range

Human Following by an Omnidirectional Mobile Robot Using Maps Built from Laser Range-Finder Measurement

2010 ◽  
Vol 22 (1) ◽  
pp. 28-35 ◽  
Author(s):  
Takashi Ogino ◽  
◽  
Masahiro Tomono ◽  
Toshinari Akimoto ◽  
Akihiro Matsumoto ◽  
...  
Keyword(s):  
Mobile Robot ◽  
Indoor Environment ◽  
Laser Range Finder ◽  
Map Building ◽  
Range Finder ◽  
Scan Matching ◽  
Laser Range ◽  
Omnidirectional Mobile Robot ◽  
Simultaneous Acquisition

This paper deals with map building from laser range finder measurement in an unknown indoor environment and its application to human following by an omnidirectional mobile robot. After reviewing basic strategies of human following by a mobile robot involving simultaneous acquisition of indoor map and robot location acquisition, we implemented “pseudo” odometry, rather than conventional odometry, for the omnidirectional mobile robot, using this information to improve scan-matching calculation accuracy. We then conducted experiments in which the robot followed a pedestrian. We confirmed that the robot could follow different pedestrian trajectories if walking was slow, and that our approach effectively improved scan matching calculation accuracy.

scholarly journals PROBABILISTIC MODEL OF LASER RANGE FINDER FOR THREE DIMENSIONAL GRID CELL IN CLOSE RANGE ENVIRONMENT

2016 ◽  
Vol 17 (1) ◽  
pp. 63-82 ◽  
Author(s):  
Hafiz b Iman ◽  
NAHRUL KHAIR ALANG MD RASHID
Keyword(s):  
Probabilistic Model ◽  
Incident Angle ◽  
Three Dimensional ◽  
Grid Cell ◽  
Normal Density ◽  
Laser Range Finder ◽  
Map Building ◽  
Range Finder ◽  
Laser Range ◽  
Close Range

The probabilistic model of a laser scanner presents an important aspect for simultaneous localization and map-building (SLAM). However, the characteristic of the beam of the laser range finder under extreme incident angles approaching 900 has not been thoroughly investigated. This research paper reports the characteristic of the density of the range value coming from a laser range finder under close range circumstances where the laser is imposed with a high incident angle. The laser was placed in a controlled environment consisting of walls at a close range and 1000 iteration of scans was collected. The assumption of normal density of the metrical data collapses when the beam traverses across sharp edges in this environment. The data collected also shows multimodal density at instances where the range has discontinuity. The standard deviation of the laser range finder is reported to average at 10.54 mm, with 0.96 of accuracy. This significance suggests that under extreme incident angles, a laser range finder reading behaves differently compared to normal distribution. The use of this information is crucial for SLAM activity in enclosed environments such as inside piping grid or other cluttered environments.KEYWORDS:   Hokuyo UTM-30LX; kernel density estimation; probabilistic model  

Localization and map building using laser range sensors in outdoor applications

2000 ◽  
Vol 17 (10) ◽  
pp. 565-583 ◽  
Author(s):  
Jose Guivant ◽  
Eduardo Nebot ◽  
Stephan Baiker
Keyword(s):  
Map Building ◽  
Laser Range ◽  
Range Sensors

scholarly journals VECTOR MAPS IN MOBILE ROBOTICS

2015 ◽  
Vol 2 (2) ◽  
pp. 22-28 ◽  
Author(s):  
Ales Jelinek
Keyword(s):  
Data Acquisition ◽  
Navigation System ◽  
Mobile Robotics ◽  
Map Building ◽  
Scan Matching ◽  
Line Extraction ◽  
Current State ◽  
Vector Maps ◽  
Localization And Mapping ◽  
University Of Technology

The aim of this paper is to provide a brief overview of vector map techniques used in mobile robotics and to present current state of the research in this field at the Brno University of Technology. Vector maps are described as a part of the simultaneous localization and mapping (SLAM) problem in the environment without artificial landmarks or global navigation system. The paper describes algorithms from data acquisition to map building but particular emphasis is put on segmentation, line extraction and scan matching algorithms. All significant algorithms are illustrated with experimental results.

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