Studies on visual perception for perceptual robotics

Studies on human visual perception measurement for perceptual robotics are described. The visual perception is mathematically modelled as a probabilistic process obtaining and interpreting visual data from an environment. The measurement involves visual openness perception in virtual reality, which has direct implications for navigation issues of actual autonomous robotics. The perception is quantified by means of a mapping function which converts a distance to an elemental perception estimate. The measurement is carried out with the averaging of the elemental perceptions in real time. This is accomplished by means of exponential averaging. The mapping function parameters are optimized uniquely by means of genetic algorithm approach where the data set for model development consists of a number of perception data samples. These are obtained from individuals who are confronted with a number of scenes and asked for their perceptual openness statements. Based on this data, a perception model is developed for a virtual robot where the simulated vision interaction of the robot with the environment is converted to visual openness estimation through the model output. The model outcome is essential visual information for the navigation of an autonomous perceptual robot.