Title :
A hierarchical map building for SLAM used in ruins environments
Author :
Nan Wang ; Shugen Ma ; Bin Li ; Minghui Wang ; Mingyang Zhao
Author_Institution :
State Key Lab. of Robot., Shenyang Inst. of Autom., Shenyang, China
Abstract :
As to the morphological characteristics of the seismic damage of the interior ruins, this paper presents a map building mechanism by using the analytic hierarchy process and proposes a hierarchical simultaneous localization and mapping (SLAM) algorithm that is based on the hybrid metric-topological map. The architecture of the ruins-oriented SLAM system consists of three layers. In the intermediate layer, the global environment is partitioned on the basis of the spectral clustering that can reduce the computational cost and ensure the global consistency. A semantic map is built in the top layer where the node identification and logic location are included. According to the characteristics of the seismic destruction, an aggregation degree of features is proposed as an identification method for building topological nodes to improve the interactivity. In the bottom layer, details of the morphology of the destruction are described as grid maps that ensure the environmental adaptability. Through experiments, the ability of environmental description and the availability at an artificial ruins environment are verified.
Keywords :
SLAM (robots); analytic hierarchy process; rescue robots; SLAM algorithm; aggregation degree of features; analytic hierarchy process; environmental adaptability; global consistency; grid maps; hierarchical map building; hierarchical simultaneous localization and mapping; hybrid metric-topological map; interior ruins; intermediate layer; logic location; map building mechanism; node identification; ruins environments; ruins-oriented SLAM system; seismic damage; seismic destruction; semantic map; spectral clustering; topological nodes; Buildings; Feature extraction; Measurement; Semantics; Simultaneous localization and mapping; Hierarchical map; Interior ruins; Map representation; Simultaneous localization and mapping;
Conference_Titel :
Intelligent Control and Automation (WCICA), 2014 11th World Congress on
DOI :
10.1109/WCICA.2014.7052925