In order to improve the quality of the bionic robot vision tracking, the new automatic tracking algorithm system is proposed in this paper. Based on the completed system hardware design and implementing scheme, the scene noise is removed by adaptive wiener filtering. Through the improved sequential particle filter algorithm, the dynamic target tracking is realized. The experiment result shows that the improved algorithm system still can lock the dynamic target accurately under the condition of that the outer contour of target changing and the partial occlusion existing.
Aiming at completing search task under disaster condition problems, an optimizing strategy based on multi-sensor 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
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