Global Symbolic Maps from Local Navigation

Abstract

In order to navigate autonomously, most robot sys-tems are provided with some sort of global terrain map. To make storage practical, these maps usually have a high-level symbolic representation of the terrain. The robot’s symbolic map is then used to plan a local path. This paper describes a system which uses the reverse (and perhaps more natural) process. This system pro-cesses local sensor data in such a way as to allow ef-ficient, reactive local navigation. A byproduct of this navigation process is an abstraction of the terrain in-formation which forms a global symbolic terrain map of the terrain through which the robot has passed. Since this map is in the same format as that used by the local navigation system, the map is easy for the sys-tem to use, augment, or correct. Compared with the data from which the maps are created, the maps are very space efficient, and can be modified, or used for navigation in real-time. Experiments with this system, both in simulation, and with a real robot operating in natural terrain, are described.

Cite

Text

Miller and Slack. "Global Symbolic Maps from Local Navigation." AAAI Conference on Artificial Intelligence, 1991.

Markdown

[Miller and Slack. "Global Symbolic Maps from Local Navigation." AAAI Conference on Artificial Intelligence, 1991.](https://mlanthology.org/aaai/1991/miller1991aaai-global/)

BibTeX

@inproceedings{miller1991aaai-global,
  title     = {{Global Symbolic Maps from Local Navigation}},
  author    = {Miller, David P. and Slack, Marc G.},
  booktitle = {AAAI Conference on Artificial Intelligence},
  year      = {1991},
  pages     = {750-755},
  url       = {https://mlanthology.org/aaai/1991/miller1991aaai-global/}
}