The purpose of this paper is to present a case study of the development, implementation and performance analysis of an autonomous flight control strategy for a 1-meter small-sized unmanned aerial vehicle. Firstly, a learning algorithm based open-loop control is proposed by simulating a skilled human operator's manipulation of the aircraft. This is aimed to generate a set of command data inputs and investigate the multi-channel control characteristics with the open-loop control. Secondly, a feedforward plus a proportional and derivative (PD) feedback control is employed to control the vehicle in following the command data to complete the loitering flight. The PD control gains are tuned automatically according to the attitude of the vehicle using the fuzzy logic theory. Thirdly, autonomous flight experiments conducted on a 1-meter small-sized aerial vehicle demonstrated the effectiveness of the proposed method.

Heat map is an important tool for eye tracking data analysis and visualization. It is very intuitive to express the area watched by observer, but ignores saccade information that expresses gaze shift. Based on conventional heat map generation method, this paper presents a novel heat map generation method for eye tracking data. The proposed method introduces a mixed data structure of fixation points and saccades, and considers heat map deformation for saccade type data. The proposed method has advantages on indicating gaze transition direction while visualizing gaze region.