Author: Pütz
Year: 2016
- 3D triangular mesh with pc
- used for traversability and roughness on uneven ground
- octree maps can be used in a ros package for planning (= occupancy map)
- triangle mesh are more flexible: Rough terrain reconstruction for rover motion planning
- take as input an arbitrary mesh (here mesh generated with Organized fast mesh)
- Navigation mesh generation (height, roughness and co) that check for lethal contexts with safety thresholds
- Graph edge region smoothing around lethal regions
- outlier removal
- organized point cloud: point stored in a
$\theta$ and$\phi$ 2D matrix structure = depth image (enables fast and robust normal estimation) - mesh generation as in Rough terrain reconstruction for rover motion planning with a rule to filter shadow edges
- two graphs: a triangle graph and a vertex graph
- for each edges a cost function taking into account: distance between vertices, local roughness, height difference or riskiness
- local roughness computed as an average fluctuation of normals in a neighbourhood
- height difference is defined as the maximum difference in the
$z$ direction in a vincinity around a vertex$v$ $$ b(v) = \underset{u \in \mathcal{N}(v)}{max} \left | \frac{(p(u) - p(v)).z}{|z|} \right | $$ - then standard graph search algorithm can be applied for path planning
- heavy roughness and heigth, bound of the mesh are marked as lethal
- inflation algorithm around lethal region to smooth the mesh
- A* search on the graph for path planning
- velocity command can be deduced by height and roughness
- 3D scans in a stop and go fashion with 2D Lidar
- low cost computation, smooth planned path
- classification based on local height is not enought