Automatic generation of modules of object categorization for autonomous mobile robots
Anna Gorbenko · AIP conference proceedings · 2013
Many robotic tasks require advanced systems of visual sensing. Robotic systems of visual sensing must be able to solve a number of different complex problems of visual data analysis. Object categorization is one of such problems. In this paper, we propose an approach to automatic generation of computationally effective modules of object categorization for autonomous mobile robots. This approach is based on the consideration of the stack cover problem. In particular, it is assumed that the robot is able to perform an initial inspection of the environment. After such inspection, the robot needs to solve the stack cover problem by using a supercomputer. A solution of the stack cover problem allows the robot to obtain a template for computationally effective scheduling of object categorization. Also, we consider an efficient approach to solve the stack cover problem. In particular, we consider an explicit reduction from the decision version of the stack cover problem to the satisfiability problem. For different satisfiability algorithms, the results of computational experiments are presented.