scholarly journals Performance Analysis of an Indoor Localization and Mapping System Using 2D Laser Range Finder Sensor

2018 ◽  
Author(s):  
Mounia Janah ◽  
Yasutaka Fujimoto
Keyword(s):  
Performance Analysis ◽  
Indoor Localization ◽  
Laser Range Finder ◽  
Range Finder ◽  
Laser Range ◽  
Localization And Mapping ◽  
Mapping System

Landmark detection and localization for mobile robot applications: a multisensor approach

Robotica ◽  
2009 ◽  
Vol 28 (5) ◽  
pp. 663-673 ◽  
Author(s):  
Dilan Amarasinghe ◽  
George K. I. Mann ◽  
Raymond G. Gosine
Keyword(s):  
The Other ◽  
Laser Range Finder ◽  
Fusion Method ◽  
Range Finder ◽  
Landmark Detection ◽  
Laser Range ◽  
Localization And Mapping ◽  
Laser Data ◽  
Single Sensor ◽  
Detection And Localization

SUMMARYThis paper describes a landmark detection and localization using an integrated laser-camera sensor. Laser range finder can be used to detect landmarks that are direction invariant in the laser data such as protruding edges in walls, edges of tables, and chairs. When such features are unavailable, the dependant processes will fail to function. However, in many instances, larger number of landmarks can be detected using computer vision. In the proposed method, camera is used to detect landmarks while the location of the landmark is measured by the laser range finder using laser-camera calibration information. Thus, the proposed method exploits the beneficial aspects of each sensor to overcome the disadvantages of the other sensor. While highlighting the drawbacks and limitations of single sensor based methods, an experimental results and important statistics are provided for the verification of the affectiveness sensor fusion method using Extended Kalman Filter (EKF) based simultaneous localization and mapping (SLAM) as an example application.

scholarly journals DEVELOPMENT OF A NEW LOW-COST INDOOR MAPPING SYSTEM – SYSTEM DESIGN, SYSTEM CALIBRATION AND FIRST RESULTS

2016 ◽  
Vol XLI-B5 ◽  
pp. 55-62
Author(s):  
T. P. Kersten ◽  
D. Stallmann ◽  
F. Tschirschwitz
Keyword(s):  
Laser Scanning ◽  
Low Cost ◽  
Design System ◽  
Raspberry Pi ◽  
Test Field ◽  
Laser Range Finder ◽  
Range Finder ◽  
System Calibration ◽  
Laser Range ◽  
Mapping System

For mapping of building interiors various 2D and 3D indoor surveying systems are available today. These systems essentially differ from each other by price and accuracy as well as by the effort required for fieldwork and post-processing. The Laboratory for Photogrammetry & Laser Scanning of HafenCity University (HCU) Hamburg has developed, as part of an industrial project, a lowcost indoor mapping system, which enables systematic inventory mapping of interior facilities with low staffing requirements and reduced, measurable expenditure of time and effort. The modelling and evaluation of the recorded data take place later in the office. The indoor mapping system of HCU Hamburg consists of the following components: laser range finder, panorama head (pan-tilt-unit), single-board computer (Raspberry Pi) with digital camera and battery power supply. The camera is pre-calibrated in a photogrammetric test field under laboratory conditions. However, remaining systematic image errors are corrected simultaneously within the generation of the panorama image. Due to cost reasons the camera and laser range finder are not coaxially arranged on the panorama head. Therefore, eccentricity and alignment of the laser range finder against the camera must be determined in a system calibration. For the verification of the system accuracy and the system calibration, the laser points were determined from measurements with total stations. The differences to the reference were 4-5mm for individual coordinates.

Sensor Agent Robot with Servo-Accelerometer for Structural Health Monitoring

2013 ◽  
Vol 558 ◽  
pp. 289-296
Author(s):  
Tatsuya Akiba ◽  
Nobukazu Lee ◽  
Akira Mita
Keyword(s):  
Structural Health Monitoring ◽  
Health Monitoring ◽  
Laser Range Finder ◽  
Range Finder ◽  
Laser Range ◽  
Good Data ◽  
Localization And Mapping ◽  
Acceleration Data ◽  
Floor Vibrations ◽  
The Cost

SHM systems are becoming feasible with the growth of computer and sensor technologies during the last decade. However, high implantation cost prevents SHM from becoming common in general buildings. The reason of this high cost is partially due to many accelerometers. In this research, we propose a mobile sensor agent robot with accelerometers and a laser range finder (LRF). If this robot can properly measure accurate acceleration data, the cost of SHM would be cut down and the SHM systems would become common. Our goal is to develop a platform for SHM using the sensor agent robot. We designed the prototype robot to detect the floor vibrations and acquire the micro tremor information correctly. When the sensor agent robot is set in the mode of acquiring the data, the dynamics of the robot should be tuned not to be affected by its flexibility. To achieve this purpose the robot frame was modified to move down to the floor and to provide enough rigidity to obtain good data. In addition to this mechanism, we tested an algorithm to know the location of the robot and the map of the floor correctly to be used in the SHM system using the LRF and Simultaneously Localization and Mapping (SLAM).

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