DocumentCode :
1800334
Title :
Terrain typing for real robots
Author :
Davis, Ian Lane ; Kelly, Alonzo ; Stentz, Anthony ; Matthies, Larry
Author_Institution :
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
fYear :
1995
fDate :
25-26 Sep 1995
Firstpage :
400
Lastpage :
405
Abstract :
Many robotics tasks require an ability to determine quickly the nature of the terrain surrounding the robot. While much attention has been given to the general problem of terrain typing, the problem of effective real-time terrain typing remains open. For robot missions such as construction site work, military reconnaissance, hazardous waste removal, and planetary exploration this problem must be addressed. In particular, for cross country navigation with a wheeled vehicle, the robot needs to know where the vegetation is and where the rigid obstacles are because frequently the optimal, if not the only, path will pass through vegetation. Our groups have independently researched the problem of finding vegetation in a scene, and have developed systems tuned to the specific demands of real-time terrain typing for robots. This paper looks at three classifiers of increasing dimensionality and describes their applicability to different aspects of the terrain typing problem
Keywords :
image classification; image colour analysis; navigation; neural nets; object recognition; real-time systems; robot vision; colour images; cross country navigation; image classifiers; neural networks; real-time systems; robot vision; terrain typing; vegetation; wheeled vehicle; Aircraft navigation; Hidden Markov models; Laboratories; Mobile robots; Pixel; Propulsion; Robot kinematics; Roentgenium; Vegetation mapping; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Vehicles '95 Symposium., Proceedings of the
Conference_Location :
Detroit, MI
Print_ISBN :
0-7803-2983-X
Type :
conf
DOI :
10.1109/IVS.1995.528315
Filename :
528315
Link To Document :
بازگشت