Abstract
Exploring large, unknown, and unstructured environments is challenging for Unmanned Aerial Vehicles (UAVs), but they are valuable tools to inspect large structures safely and efficiently. The Lazy Theta* path-planning algorithm is revisited and adapted to generate paths fast enough to be used in real time and outdoors in large 3D scenarios. In real unknown scenarios, a given minimum safety distance to the nearest obstacle or unknown space should be observed, increasing the associated obstacle detection queries, and creating a bottleneck in the path-planning algorithm. We have reduced the dimension of the problem by considering geometrical properties to speed up these computations. On the other hand, we have also applied a non-regular grid representation of the world to increase the performance of the path-planning algorithm. In particular, a sparse resolution grid in the form of an octree is used, organizing the measurements spatially, merging voxels when they are of the same state. Additionally, the number of neighbors is trimmed to match the sparse tree to reduce the number of obstacle detection queries. The development methodology adopted was Test-Driven Development (TDD) and the outcome was evaluated in real outdoors flights with a multirotor UAV. In the results, the performance shows over 90 percent decrease in overall path generation computation time. Furthermore, our approach scales well with the safety distance increases.
Highlights
The role of Unmanned Aerial Vehicles (UAVs) as tools in human activities only begins to unfold
The main contributions of the paper are (1) presenting an any-angle path-planning algorithm that generates three-dimensional paths with an obstacle-free flight corridor around the trajectory, implemented over sparse grids; (2) introducing a two-phased approach to obstacle detection that qualifies Lazy Theta* for real-time, onboard usage as both a local and global planner; (3) refine neighborhood generation by taking into account the multi-resolution nature of the octree; (4) adoption of the methodology Test-Driven Development (TDD) paired with smart monkey testing
This paper builds upon the work presented in the article [7], which describes the implementation of Lazy Theta* using octomap as the world representation
Summary
The role of Unmanned Aerial Vehicles (UAVs) as tools in human activities only begins to unfold. Examples of tasks aided by UAVs are package transportation [1,2], industrial inspection [3,4,5,6,7,8], scene reconstruction [9,10,11], and environmental monitoring [12,13,14]. These applications, in daily life, take place outside controlled environments. Examples are sewer exploration [5], bridge inspection [4], and forest exploration [15]
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