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|Title:||Metric mapping and topo-metric graph learning of urban road network|
Ang Jr., M.H.
|Citation:||Qin, B.,Chong, Z.J.,Bandyopadhyay, T.,Ang Jr., M.H. (2013). Metric mapping and topo-metric graph learning of urban road network. IEEE Conference on Robotics, Automation and Mechatronics, RAM - Proceedings : 119-123. ScholarBank@NUS Repository. https://doi.org/10.1109/RAM.2013.6758570|
|Abstract:||A road map serves as a model of the road network, which is especially desired for a vehicle performing autonomous navigation in urban road environment. This paper first introduces a metric mapping algorithm for urban roads, which generates an occupancy grid map of road surfaces and boundaries. Based on the metric map, we further propose an approach to extract a topo-metric graph which captures both topological and metric information of the road network. As a detailed model of the urban roads, the metric map can be used for obstacle avoidance and local path planning, while the topo-metric graph as a compact representation that can be used for some high-level reasoning processes. Our proposed algorithms are tested in real experiments, and have shown good results. © 2013 IEEE.|
|Source Title:||IEEE Conference on Robotics, Automation and Mechatronics, RAM - Proceedings|
|Appears in Collections:||Staff Publications|
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