Multi-uav Coverage Path Planning for Reconstruction of 3D Structures
Abstract
Path planning is the generation of paths for the robots to navigate based on some constraints. Coverage path planning is where the robots needs to cover an entire workspace for various applications like sensing, inspection and so on. Though there are numerous works on 2D coverage and also coverage using a single robot, the works on 3D coverage and multi-agents are very limited. This thesis makes several contributions to multi-agent path planning for 3D structures. Motivated by the inspection of 3D structures, especially airplanes, we present a 3D coverage path planning algorithm for a multi-UAV system. We propose a unified method, where the viewpoints selection and path generation are done simultaneously for multiple UAVs. The approach is scalable in terms of number of UAVs and is also robust to models with variations in geometry. The proposed method also distributes the task uniformly amongst the multiple UAVs involved and hence making the best use of the robotics team. The uniform task distribution is an integral part of the path planner. Various performance measures of the paths generated in terms of coverage, path length and time also has been presented.
Degree
M.Sc.
Advisors
Min, Purdue University.
Subject Area
Aerospace engineering|Robotics|Transportation
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