A Method for Indoor Robots Visual Perception Based on Multi-Feature Fusion

For improving environmental visual perception of indoor robots more accurate and faster, a new model based on image multi-feature fusion is proposed. The hierarchical match mode is used to match real-time collected images of indoor robot with various multi-directional and multi-state images in a database. After establishing a database of 1000 images, average accuracy, average recall ratio and average time are used to evaluate the algorithm. Experimental results show that the algorithm can accurately and efficiently identify target images. Comparing with single feature visual perception, the algorithm not only achieves higher matching accuracy, but also meets the real-time requirement of robots.