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.
This paper represents the relationship between the stability of stairs climbing and the centroid position of the search and rescue robot. The robot system is considered as a mass point-plane model and the kinematics features are analyzed to find the relationship between centroid position and the maximal pitch angle of stairs the robot could climb up. A computable function about this relationship is given in this paper. During the stairs climbing, there is a maximal stability-keeping angle depends on the centroid position and the pitch angle of stairs, and the numerical formula is developed about the relationship between the maximal stability-keeping angle and the centroid position and pitch angle of stairs. The experiment demonstrates the trustworthy and correction of the method in the paper.
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