Cost-Efficient Global Robot Navigation in Rugged Off-Road Terrain

被引：0
|
作者：
Braun, T. [1 ]
机构：
[1] Univ Kaiserslautern, Dept Comp Sci, Robot Res Lab, POB 3049, D-67653 Kaiserslautern, Germany
来源：
KUNSTLICHE INTELLIGENZ | 2011年 / 25卷 / 02期
关键词：
Robot navigation; Topological map; Traversability cost learning;
D O I：
10.1007/s13218-011-0088-9
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The thesis "Cost-Efficient Global Robot Navigation in Rugged Off-Road Terrain" proposes a global robot navigation concept for rugged off-road terrain which is robust against inaccurate self-localization and scalable to large environments, but also cost-conscious, e.g. able to generate navigation paths which optimize a cost measure closely related to terrain traversability. The thesis contributes a set of new techniques to integrate cost-consciousness into a primarily topological navigation scheme. Also, novel methods to learn and optimize cost estimates from experience are developed.
引用
收藏
页码：173 / 177
页数：5
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