DocumentCode
2350510
Title
Consecutive scanning based obstacle detection and probabilistic navigation of a mobile robot
Author
Lee, Jae-Yong ; Lee, Sooyong
Author_Institution
Dept. of Mech. Eng., Texas A&M Univ., College Station, TX, USA
Volume
4
fYear
2003
fDate
27-31 Oct. 2003
Firstpage
3510
Abstract
This paper presents the obstacle detection algorithm based on the consecutive range sensor scanning scheme and the probabilistic navigation for an mobile robot. For a known environment, a mobile robot scans the environment using the range sensor which can rotate 360°. The environment is rebuilt using nodes of two adjacent walls, and an obstacle is detected by comparing characteristic points of both the known environment and the scanned data set. It is very useful for detecting the moving obstacle. By comparing two data sets, the movement of an obstacle is extracted. Furthermore, the consecutive scanning data set provides obstacle information in unknown environment. Geometric comparison between the two consecutive data sets is used to detect the obstacles and the algorithm is presented with both simulation and experimental results. After the obstacle information is extracted from the consecutive scanning, the path is rebuilt by checking the collision probability.
Keywords
collision avoidance; image sensors; mobile robots; navigation; position control; robot vision; spatial reasoning; collision avoidance; collision probability; consecutive range sensor scanning; geometric comparison; obstacle detection algorithm; obstacle information; position control; probabilistic mobile robot navigation; robot vision; scanned data set; Cameras; Data mining; Mechanical sensors; Mobile robots; Navigation; Robot sensing systems; Robot vision systems; Sensor phenomena and characterization; Sensor systems; Sonar;
fLanguage
English
Publisher
ieee
Conference_Titel
Intelligent Robots and Systems, 2003. (IROS 2003). Proceedings. 2003 IEEE/RSJ International Conference on
Print_ISBN
0-7803-7860-1
Type
conf
DOI
10.1109/IROS.2003.1249699
Filename
1249699
Link To Document