The process how to acquire knowledge about the operating environment belongs to the most challenging problems that autonomous mobile robots solve. The quality of the model depends on a number and the art of sensors used and on a precision the robot knows its position in the environment. The occupancy grid belongs to the most common low-level models of the environment being considered for highly robust approach for fusion of noisy data and for fusion of data from different kinds of sensor. This paper primarily introduces a novel method for building an occupancy grid from a monocular color camera with its’ automatic calibration. The other part of the work describes a method for fusion of camera data with data from a sonar rangefinder. The presented methods were experimentally verified with an indoor experimental robot at the Czech Technical University facilities.