Layered costmaps is a method to create and update maps for robot navigation and path planning proposed by David V. Lu in 2014. [1] During robot navigation, layered costmaps can abstract the realistic environment around the robot into maps that can be comprehended by robot navigation methods. The method consists of more than one layer of costmaps, each of which describes obstacles with different properties. Each layered costmap consists of grids and is represented as a matrix, the values of the matrix elements are related to the risks of grids (the higher the value,the greater the risk and the deeper the colour in the grid). In the layered costmap, the colour of a grid indicates the risk of moving through that grid. There is a high probability of robot collision when the robot moves through a grid with deep colour. When updating a layered costmap, only the area covered by the sensors (such as Lidar) in the map is updated, rather than the entire map.
- ^ Lu, David V.; Hershberger, Dave; Smart, William D. (September 2014). "Layered costmaps for context-sensitive navigation". 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems. pp. 709–715. doi:10.1109/IROS.2014.6942636. ISBN 978-1-4799-6934-0.