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67.3%。 A method of branch identification for citrus harvesting robot was proposed. According to the characteristics of obstacle that citrus harvesting robot met, such as branch, the 3-D information of obstacle was restored by extracting and processing the skeleton of obstacle image. The branch region was obtained using image segmentation, morphologic processing and region labeling. Then the skeleton of obstacle was extracted by thinning, and the feature points such as endpoint and branch point of the skeleton was found out, to record their connecting relationship. Finally the 3-D information of obstacle was restored by stereo matching on feature points. Experimental results showed that the identification accuracy of obstacle can reach 67.3%, and the identification error ratio is increased when the actual distance of obstacle is more than 1.5m.