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摘要
When a human pilot operates an unmanned aerial vehicle (UAV), there is a brain body and vision (physiological) coordination taking place between the human and the aircraft. Mainly, the UAV control-position-orientation interactions, referred as the aerophysics (similar to biophysics) take place due to pilot's physiological interventions. In this context, it becomes important to connect neural network based UAV control, camera vision based sensing, etc., with physiology. A specific problem associated with physiology is obstacle avoidance. When an obstacle is sensed, the human brain instantly dumps the existing thoughts that would steer the vehicle to collide with the obstacle's geospatial position. Then, other positions are reconfigured to avoid the obstacle for which the UAV is steered with biostability (stable transcriptions of the reconfigurable controllers). Since the controllers are linear, they should be capable of handling the nonlinear UAV at decision points where reconfiguration takes place. In this paper, such nonlinear trajectories with transcriptions at decision points to reconfigure a set of geospatial coordinates are considered. Then tools to interpret potential human physiology that would establish neural networks and camera vision connections are presented.
- 出版日期2017-12
