University of Maryland

Risk-based Path Planning for Unmanned Aerial Systems

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Research Team: Shapour Azarm, Jeffrey W. Herrmann, and Eliot Rudnick-Cohen.

Funding Source: This project received funding from the U.S. Navy.

Background and Project Objectives

This research project is studying the problem of improving the safety of UAS operations by finding safe, efficient paths.

Operating unmanned aerial vehicles (UAVs) over inhabited areas requires mitigating the risk to persons on the ground. Because the risk depends upon the flight path, UAV operators need approaches that can find low-risk flight paths between the mission's start and finish points. Because the flight paths with the lowest risk could be excessively long and indirect, UAV operators are concerned about the tradeoff between risk and flight time.


We developed a risk assessment technique and bi-objective optimization methods to find safe (low-risk) and efficient (short) solutions (flight paths) and conducted computational experiments to evaluate the relative performance of the methods (their computation time and solution quality). The methods were a network optimization approach that constructed a graph for the problem and used that to generate initial solutions that were then improved by a local approach and a greedy approach and a fourth method that did not use the network solutions. The approaches that improved the solutions generated by the network optimization step performed better than the optimization approach that did not use the network solutions.

Related Publications

Last updated on August 30, 2018, by Jeffrey W. Herrmann.