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Layered Costmaps for Context-Sensitive Navigation

David V. Lu, Dave Hershberger, and William D. Smart.
In "Proceedings of the IEEE/RSJ International Conference on Robots and Systems (IROS)", pages 709-715, Chicago, IL, 2014.

Many navigation systems, including the ubiquitous ROS navigation stack, perform path-planning on a single costmap, in which the majority of information is stored in a single grid. This approach is quite successful at generating collision-free paths of minimal length, but it can struggle in dynamic, people-filled environments when the values in the costmap expand beyond occupied or free space.

We have created and implemented a new method called layered costmaps, which work by separating the processing of costmap data into semantically-separated layers. Each layer tracks one type of obstacle or constraint, and then modifies a master costmap which is used for the path planning. We show how the algorithm can be integrated with the open-source ROS navigation stack, and how our approach is easier to fine-tune to specific environmental contexts than the existing monolithic one. Our design also results in faster path planning in practical use, and exhibits a cleaner separation of concerns that the original architecture. The new algorithm also makes it possible to represent complex cost values in order to create navigation behavior for a wide range of contexts.

@inproceedings{iros2014a,
  author = {Lu, David V. and Hershberger, Dave and Smart, William D.},
  title = {Layered Costmaps for Context-Sensitive Navigation},
  booktitle = {Proceedings of the {IEEE/RSJ} International Conference on Robots and Systems ({IROS})},
  pages = {709--715},
  address = {Chicago, IL},
  year = {2014}
}