Route space detection of industrial indoor vehicle with joint extended histograms of oriented gradients(EHOG)

This paper introduces the method of detecting a route space for an industrial indoor vehicle. The vehicles work in many industrial fields, e.g., a semiconductor production and a car assembly factory. The detection of the route space under illuminant disturbance is an important problem for the industrial vehicle robot. The industrial vehicle has to move to the same areas in a factory. For these works, the usual industrial vehicle, e.g., an automated guided vehicle (AGV), is transported in path line. However, this conventional system of AGV is not a flexible method to change a goal position. On the other hand, a mobile robot, e.g., a wheeled robot, can move without a line or rail for the path, and an auto vehicle runs on the urban road. These robots use multi-sensors. However, the industrial vehicle intent to decrease the number of sensors for the cost down. For the reason, we propose a detection of a passable route space for an AGV. We proposed the detection method using a stereo camera in order to move the AGV without path line. Our proposed method is based on the joint extended HOG (joint EHOG) and AdaBoost algorithm. EHOG has the robustness for the illuminant disturbance, however, the EHOG is not robust for variable image size. The proposed method has the robustness to the illuminant disturbance and to variable image sizes of the target. The proposed method decreases the number of the wrong detection by weighting factors to a weak classifier and combines the many detection areas by the mean shift clustering. The experimental results show the effectiveness of the proposed method for a route space detection and we finally show the future works.