Aerial vehicle trajectory design for spatio-temporal task aggregation

An optimal design method for generating a flight path passing through specified waypoints while satisfying the task points sent by the ground operators is proposed in this paper. Each specified waypoint is reached exactly at the specified location and time while intermediate waypoints are generated in such a way that they satisfy the task points, with highest benefit measure, i.e., satisfying tasks with higher task priority and QoS desired. Generated waypoints are points from where imagery data associated with the tasks are collected, and these task points are aggregated by the TABUM (Task Aggregation Based on Utility Metric) approach by considering the factors such as task points' priorities, image sensors capabilities and the deviation required from the shortest path from the waypoint. We generate a flight trajectory, which is a collection of predefined waypoints and generated waypoints by taking the velocities and maneuverability of the aerial vehicle into consideration while ensuring that the vehicle avoids the no-fly zones. We finally frame the problem of trajectory generation in a constrained environment as an optimization problem and solve it by increasing the benefit measure and decreasing the cost measure (i.e., deviation). We performed simulation based experiments to show the effect of the utility metric threshold value and compared the performance of the vehicles' trajectory with fixed-wing flight maneuverability and quad-copter maneuverability capabilities.