Abstract: Considering the low accuracy and poor adaptability of the existing scene recognition methods, the autonomous developmental neural network is applied to the robot scene recognition task, and two scene recognition methods combining the autonomous developmental network and multi-sensor fusion are proposed, namely, the robot scene recognition method based on weighted Bayesian fusion, and the scene recognition method based on data fusion of the same autonomous developmental network architecture, where the multi-sensor information is fused in the decision-making layer and the data layer, respectively, so as to improve the accuracy of scene recognition. Meanwhile, the autonomous developmental network improves the adaptability of the recognition method for various complex scenes. The proposed scene recognition method is tested and analyzed, which proves its effectiveness and practicability. In addition, the proposed method achieves better accuracy in scene recognition due to more efficient use of collected data through data fusion in the same network architecture.