The ability of autonomous navigation of the humanoid robot under unknown environment is very important to real-life applications. EKF-SLAM based on the camera recognition and laser detection for humanoid robot NAO is presented in this paper. Camera recognition is used to recognize if the object is a landmark. Because the computational resources needed for the feature-based position estimation are quite expensive, the laser instead of the camera provides the position of the landmark. A fractional

This article proposes a novel method that combines real-time image recognition with choosing target object real-time localization in unknown environment. The position information of the object recognized as a target is provided by laser, which avoids collecting all the objects position information in the environment. This can save the computation resource and improve the real time. Furthermore, this article realizes the autonomous back and forth navigation in unknown environment and companies voice prompt and intelligent searching of the target object. This will set up a basis on building a complete environment map. Finally, the experiments show the validness of the proposed method and improve the intelligence of the environment information collection.

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