School of Mechanical & Power Engineering, Harbin University of Science and Technology, Harbin, China

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Abstract—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.

Index Terms—Polymerization Kalman filter, information fusion, search and rescue robot, embedded system.

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Cite: Peng Wang, Wenhao Jiang, Xin Li, Shaochen Kang, Jinglei Xin, "Research for Multi-sensor Information Fusion Algorithm of Search and Rescue Robot Based on Embedded Control Network," Journal of Computers vol. 7, no. 5, pp. 1196-1203, 2012.