Path Planning for Optimal Coverage of Areas with Nonuniform Importance

TL;DR

This paper introduces an optimization algorithm for UAV path planning that maximizes coverage and importance score in challenging regions with nonuniform importance, ensuring efficient battery use and return to start.

Contribution

It presents a novel multi-objective optimization approach for UAV coverage in hazardous regions with nonuniform importance, using sequential quadratic programming.

Findings

The algorithm effectively maximizes coverage and importance score.

Simulations demonstrate efficient battery use and optimal path planning.

The method is applicable to real-world volcanic region coverage.

Abstract

Coverage of an inaccessible or challenging region with potential health and safety hazards, such as in a volcanic region, is difficult yet crucial from scientific and meteorological perspectives. Areas contained within the region often provide valuable information of varying importance. We present an algorithm to optimally cover a volcanic region in Hawai`i with an unmanned aerial vehicle (UAV). The target region is assigned with a nonuniform coverage importance score distribution. For a specified battery capacity of the UAV, the optimization problem seeks the path that maximizes the total coverage area and the accumulated importance score while penalizing the revisiting of the same area. Trajectories are generated offline for the UAV based on the available power and coverage information map. The optimal trajectory minimizes the unspent battery power while enforcing that the UAV returns to its starting location. This multi-objective optimization problem is solved by using sequential quadratic programming. The details of the competitive optimization problem are discussed along with the analysis and simulation results to demonstrate the applicability of the proposed algorithm.