Abstract： In view of the wheeltracked robot’s road status recognition under the unknown circumstance, a new identification method was proposed based on multi information fusion, and the method compounded with support vector machine (SVM) theory and DempsterShafer (DS) evidence theory. First, a data acquisition system composed of ultrasonic sensors and infrared sensors was designed in order to get the features of the road condition. Then on the basis of Platt posteriori probability, the multiclass posteriori probability model and BPA function were constructed. Finally, experiments with SVM+DS fusion and identification method were carried out to identify the three typical road conditions. The results showed that flat road, slope and step conditions could be identified effectively, hence the method could satisfy the performance requirement of the wheeltracked robot.