As the potential for deploying low-flying unmanned aerial vehicles (UAVs) in urban spaces increases, ensuring their safe operations is becoming a major concern. Given the uncertainties in their operational environments caused by wind gusts, degraded state of health, and probability of collision with static and dynamic objects, it becomes imperative to develop online decision-making schemes to ensure safe flights. In this paper, we propose an online decision-making framework that takes into account the state of health of the UAV, the environmental conditions, and the obstacle map to assess the probability of mission failure and re-plan accordingly. The online re-planning strategy considers two situations: (1) updating the current trajectory to reduce the probability of collision; and (2) defining a new trajectory to find a new safe landing spot, if continued flight would result in risk values above a pre-specified threshold. The re-planning routine uses the differential evolution optimization method and takes into account the dynamics of the UAV and its components as well as the environmental wind conditions. The new trajectory generation routine combines probabilistic road-maps with B-spline smoothing to ensure a dynamically feasible trajectory. We demonstrate the effectiveness of our approach by running UAV flight simulation experiments in urban scenarios.
Online decision making, Unmanned aerial vehicles, Urban scenarios
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