A decision-making framework for safe operations of unmanned aerial vehicles in urban scenarios



Published Nov 3, 2020
Marcos Quiñones Timothy Darrah Gautam Biswas Chetan Kulkarni


This paper presents a decision-making scheme at the level of individual unmanned aerial vehicles (UAVs) with the goal of maintaining safe operations for urban mobility. The decision-making approach for a single UAV will consider the risks associated with the current trajectory given the existing environmental conditions and the state of the vehicle. The proposed scheme combines the analysis of system performance, environmental conditions, and mission level parameters for contingency management, i.e., make a determination on: (1) to abort mission and land safely; (2) re-plan current mission in full or abbreviated form; and (3) change mission.  A path planning and trajectory optimization algorithm with the goal of minimizing the overall risk of mission failure by considering a number of factors such as the uncertainties in the environment and operating state of the vehicle is proposed. We will consider the mission failure as the loss of control of the vehicle resulting in a collision with other objects or a crash into the ground. An offline part of the framework generates an initial mission plan by considering the state of the vehicle, the environmental, conditions, and the static features of a map of the environment. Once the vehicle takes off, the risk of mission’ failure associated with the remaining trajectory is re-computed in an online framework to assess whether re-planning is required or not. A key challenge that we consider in this paper is to study the effects of multiple interacting subsystems of the UAV on system performance, especially under degraded conditions.

How to Cite

Quiñones, M., Darrah, T. ., Biswas, G., & Kulkarni, C. (2020). A decision-making framework for safe operations of unmanned aerial vehicles in urban scenarios. Annual Conference of the PHM Society, 12(1), 11. https://doi.org/10.36001/phmconf.2020.v12i1.1190
Abstract 722 | PDF Downloads 596



decision-making, unmanned aerial vehicles, path planning, optimization

Technical Research Papers

Most read articles by the same author(s)

1 2 3 > >>