DocumentCode :
1822906
Title :
Minimum throughput adaptive perception for high speed mobility
Author :
Kelly, Alonzo ; Stentz, Anthony
Author_Institution :
Robotics Inst., Carnegie Mellon Univ., Pittsburgh, PA, USA
Volume :
1
fYear :
1997
fDate :
7-11 Sep 1997
Firstpage :
215
Abstract :
For autonomously navigating vehicles, the automatic generation of dense geometric models of the environment is a computationally expensive process. Yet, analysis suggests that some approaches to mapping the environment in mobility scenarios can waste significant computational resources. This paper proposes a relatively simple method of approaching the minimum required perceptual throughput in a terrain mapping system, and hence the fastest possible update of the environmental model. We accomplish this by exploiting the constraints of typical mobility scenarios. The technique proposed will be applicable to any application that models the environment with a terrain map or other 2-1/2 D representation
Keywords :
computational complexity; computerised navigation; mobile robots; robot vision; vehicles; 2-1/2 D representation; autonomously navigating vehicles; computational expense; dense geometric models; high-speed mobility; minimum throughput adaptive perception; terrain mapping system; Land vehicles; Mobile robots; Navigation; Remotely operated vehicles; Robotics and automation; Solid modeling; Terrain mapping; Throughput; Uniform resource locators; Vehicle safety;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Robots and Systems, 1997. IROS '97., Proceedings of the 1997 IEEE/RSJ International Conference on
Conference_Location :
Grenoble
Print_ISBN :
0-7803-4119-8
Type :
conf
DOI :
10.1109/IROS.1997.649057
Filename :
649057
Link To Document :
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