A Combination of Terrain Prediction and Correction for Search and Rescue Robot Autonomous Navigation

This paper presents a novel two-step autonomous navigation method for search and rescue robot. The algorithm based on the vision is proposed for terrain identification to give a prediction of the safest path with the support vector regression machine (SVRM) trained off-line with the texture feature and color features. And correction algorithm of the prediction based the vibration information is developed during the robot traveling, using the judgment function given in the paper. The region with fault prediction will be corrected with the real traversability value and be used to update the SVRM. The experiment demonstrates that this method could help the robot to find the optimal path and be protected from the trap brought from the error between prediction and the real environment.