Sensor based motion planning: the hierarchical generalized Voronoi graph
Sensor based motion planning: the hierarchical generalized Voronoi graph
Learning metric-topological maps for indoor mobile robot navigation
Artificial Intelligence
Vision for Mobile Robot Navigation: A Survey
IEEE Transactions on Pattern Analysis and Machine Intelligence
Robot Motion Planning
Traversability Analysis and Path Planning for a Planetary Rover
Autonomous Robots
Using Real-Time Stereo Vision for Mobile Robot Navigation
Autonomous Robots
Integrating grid-based and topological maps for mobile robot navigation
AAAI'96 Proceedings of the thirteenth national conference on Artificial intelligence - Volume 2
Application of the fast marching method for outdoor motion planning in robotics
Robotics and Autonomous Systems
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This article presents a new methodology to build, in real-time, compact local and global maps for outdoor navigation. The environment information is obtained from a 3D laser range. The navigation model, called Traversable Regions Model (TRM), is based on Voronoi diagram technique but adapted to large outdoor environments, that is, the model is built from 3D data. In the manuscript we also present a novel contribution to the regions modeling field in robotics. The method allows to calculate the roughness degree of an unknown terrain based on the normal vector deviation. The parameter which measure the roughness degree is called spherical variance and it will be useful to determine the traversable areas. The model built allows defining safe trajectories depending on the robot's capabilities and the terrain properties and will represent, in a topo-geometric way, the environment as local and global maps. The methodology presented is validated in real outdoor environments with an outdoor robot developed in our lab, called $$\mathcal{G}\mathcal{O}\mathcal{L}\mathcal{I}\mathcal{A}\mathcal{T}$$ .