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

页码：173 / 177

页数：5

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