Stable Vision System for Indoor Moving Robot Using Encoder Information

This paper addresses a stable vision system for indoor moving robot using encoder information. The proposed system uses encoder signals to calculate robot motion and rotates the camera in order to fix the target on the image frame during locomotion. Since the calculation of rotating angle of the camera is based on the integration of encoder data over time, this leads to the unbounded accumulation of error. To prevent the error accumulation, vision sensor signals are used periodically to compensate for the errors. The resulting standard deviations of the rotated camera angle error were 0.94°, 0.32° and 1.55° for rotation, translation and rotation-translation combined motion while the robot heading angles have standard deviations of 23.27°, 16.56° and 48.53°, respectively. However, the system shows performance degradation in slippery ground conditions. In our experiments the errors have trends to increase with the decrease of friction coefficient between the ground and the robot wheels. Future work should overcome this problem using additional sensors such as inertial measurement units (IMUs) that are able to detect the correct robot motion even in the case of slip disturbance.