Near-Optimal Area-Coverage Path Planning of Energy-Constrained Aerial Robots With Application in Autonomous Environmental Monitoring

This article describes a Voronoi-based path generation (VPG) algorithm for an energy-constrained mobile robot, such as an unmanned aerial vehicle (UAV). The algorithm solves a variation of the coverage path-planning problem where complete coverage of an area is not possible due to path-length limits caused by energy constraints on the robot. The algorithm works by modeling the path as a connected network of mass-spring-damper systems. The approach further leverages the properties of Voronoi diagrams to generate a potential field to move path waypoints to near-optimal configurations while maintaining path-length constraints. Simulation and physical experiments on an aerial vehicle are described. Simulated runtimes show linear-time complexity with respect to the number of path waypoints. Tests in variously shaped areas demonstrate that the method can generate paths in both convex and nonconvex areas. Comparison tests with other path generation methods demonstrate that the VPG algorithm strikes a good balance between runtime and optimality, with significantly better runtime than direct optimization, lower cost coverage paths than a lawnmower-style coverage path, and moderately better performance in both metrics than the most conceptually similar method. Physical experiments demonstrate the applicability of the VPG method to a physical UAV, and comparisons between real-world results and simulations show that the costs of the generated paths are within a few percent of each other, implying that analysis performed in simulation will hold for real-world application, assuming that the robot is capable of closely following the path and a good energy model is available. Note to Practitioners-For autonomous mobile-robotics-based applications where a robot equipped with a tool or sensor is required to survey an area for inspection, monitoring, cleaning, and so on, effectively covering the area is desirable. However, for energy-constrained systems such as aerial vehicles with limited flight time, complete coverage is not possible. Presented here is a new Voronoi-based path generation algorithm that takes energy constraints into account to generate waypoints for the robot to follow in a near-optimal configuration while maintaining path-length constraints. The approach is applied in simulation and experiments for an application in environmental monitoring using unmanned aerial vehicles.

Automated summary

This article presents a Voronoi-based path generation algorithm for energy-constrained mobile robots, utilizing mass-spring-damper systems and Voronoi diagrams to optimize path generation. The algorithm showcases linear-time complexity, versatility in generating paths for various area shapes, and striking a balance between runtime and optimization performance.