Evaluation of Algorithms for indoor mobile robot self-localization through laser range finders data

2010 ◽  
Vol 43 (16) ◽  
pp. 563-568
Author(s):  
Filippo Bonaccorso ◽  
Francesco Catania ◽  
Giovanni Muscato
Keyword(s):  
Mobile Robot ◽  
Laser Range ◽  
Indoor Mobile Robot ◽  
Laser Range Finders

Development of a Laser Range Sensor for a Mobile Robot

1991 ◽  
Vol 3 (5) ◽  
pp. 373-378 ◽  
Author(s):  
Kiyoshi Komoriya ◽  
◽  
Kazuo Tani
Keyword(s):  
Mobile Robot ◽  
Autonomous Navigation ◽  
Ccd Camera ◽  
Sensor System ◽  
Beam Spot ◽  
Laser Range ◽  
Range Sensor ◽  
Good Spatial Resolution ◽  
Indoor Mobile Robot ◽  
Robot Position

External sensors which can detect environmental information are important for a mobile robot to recognize its surroundings and location. Among external sensors, range sensors are fundamental because they can directly detect the free space in which the mobile robot can move without colliding with the surrounding objects. A laser range sensor provides good spatial resolution, and it is expected to detect characteristic parts of the environment used as landmarks for recognizing robot position. This paper presents the construction of a laser range sensor system which can be implemented in a small mobile robot. The system consists of several components including laser diode, CCD camera, and mark detection hardware. Based on triangulation method, the system can detect the distance to the object's surface on which the beam spot is directed. In order to detect a landmark, such as a wall edge, the sensor system is mounted on a rotary table. By horizontally scanning, the sensor can detect wall edges with an accuracy of approximately 5mm and an orientation accuracy of approximately 1 degree within 3m. This system has been installed in an indoor mobile robot and is used for autonomous navigation control along corridors.

Development of an Autonomous Mobile Robot with Self-Localization and Searching Target in a Real Environment

2015 ◽  
Vol 27 (4) ◽  
pp. 356-364 ◽  
Author(s):  
Masatoshi Nomatsu ◽  
◽  
Youhei Suganuma ◽  
Yosuke Yui ◽  
Yutaka Uchimura
Keyword(s):  
Mobile Robot ◽  
Point Cloud ◽  
Moving Objects ◽  
Three Dimensional ◽  
Real Life ◽  
Autonomous Mobile Robot ◽  
Laser Range ◽  
Challenge Course ◽  
Laser Range Finders ◽  
Do So

<div class=""abs_img""> <img src=""[disp_template_path]/JRM/abst-image/00270004/05.jpg"" width=""200"" /> Developed autonomous mobile robot</div> In describing real-world self-localization and target-search methods, this paper discusses a mobile robot developed to verify a method proposed in Tsukuba Challenge 2014. The Tsukaba Challenge course includes promenades and parks containing ordinary pedestrians and bicyclists that require the robot to move toward a goal while avoiding the moving objects around it. Common self-localization methods often include 2D laser range finders (LRFs), but such LRFs do not always capture enough data for localization if, for example, the scanned plane has few landmarks. To solve this problem, we used a three-dimensional (3D) LRF for self-localization. The 3D LRF captures more data than the 2D type, resulting in more robust localization. Robots that provide practical services in real life must, among other functions, recognize a target and serve it autonomously. To enable robots to do so, this paper describes a method for searching for a target by using a cluster point cloud from the 3D LRF together with image processing of colored images captured by cameras. In Tsukuba Challenge 2014, the robot we developed providing the proposed methods completed the course and found the targets, verifying the effectiveness of our proposals. </span>

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