Robust world-modelling and navigation in a real world

被引:21
作者
Zimmer, UR
机构
关键词
artificial neural networks; mobile robots; self-organization; world-modelling; navigation;
D O I
10.1016/0925-2312(95)00097-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article will discuss a qualitative, topological and robust world-modelling technique with special regard to navigation tasks for mobile robots operating in unknown environments. As a central aspect, the reliability regarding error-tolerance and stability will be emphasized. Benefits and problems involved in exploration as well as in navigation tasks are discussed. The proposed method demands very low constraints for the kind and quality of the employed sensors as well as for the kinematic precision of the utilized mobile platform. Hard real-time constraints can be handled due to the low computational complexity. The principal discussions are supported by real-world experiments with the mobile robot 'ALICE'.
引用
收藏
页码:247 / 260
页数:14
相关论文
共 15 条
[11]  
MATARIE MJ, 1992, IEEE T ROB AUT, V8
[12]   LEARNING GOAL-DIRECTED SENSORY-BASED NAVIGATION OF A MOBILE ROBOT [J].
TANI, J ;
FUKUMURA, N .
NEURAL NETWORKS, 1994, 7 (03) :553-563
[13]  
WEISS G, 1994, IEEE INT C INT ROB S
[14]  
ZIMMER UR, 1994, P IIZUKA 94
[15]  
ZIMMER UR, 1994, P IEEE EUR 94 REALT