TY - JOUR
T1 - Research for multi-sensor information fusion algorithm of search and rescue robot based on embedded control network
AU - Wang, Peng
AU - Jiang, Wenhao
AU - Li, Xin
AU - Kang, Shaochen
AU - Xin, Jinglei
PY - 2012
Y1 - 2012
N2 - Aiming at completing search task under disaster condition problems, an optimizing strategy based on multisensor information fusion is proposed in this paper. Firstly, search and rescue robot control system hardware circuit is designed; secondly, embedded system software design is realized; and then, a polymerization Kalman filtering model is proposed, it uses local Kalman filter weights scheduling principle to improve system fault-tolerant ability and overall fusion performance. What's more, Adaboost algorithm realizes the multi-sensor information optimal fusion. Through simulation test experiment, the robot search traversal ability is verified under unstructured environment.
AB - Aiming at completing search task under disaster condition problems, an optimizing strategy based on multisensor information fusion is proposed in this paper. Firstly, search and rescue robot control system hardware circuit is designed; secondly, embedded system software design is realized; and then, a polymerization Kalman filtering model is proposed, it uses local Kalman filter weights scheduling principle to improve system fault-tolerant ability and overall fusion performance. What's more, Adaboost algorithm realizes the multi-sensor information optimal fusion. Through simulation test experiment, the robot search traversal ability is verified under unstructured environment.
KW - Embedded system
KW - Information fusion
KW - Polymerization Kalman filter
KW - Search and rescue robot
UR - http://www.scopus.com/inward/record.url?scp=84860291124&partnerID=8YFLogxK
U2 - 10.4304/jcp.7.5.1176-1183
DO - 10.4304/jcp.7.5.1176-1183
M3 - Article
AN - SCOPUS:84860291124
SN - 1796-203X
VL - 7
SP - 1176
EP - 1183
JO - Journal of Computers
JF - Journal of Computers
IS - 5
ER -