A distributed algorithm for mapping the graphical structure of complex environments with a swarm of robots

@inproceedings{caccavale_distributed_2017,
  address = {Singapore, Singapore},
  title = {A distributed algorithm for mapping the graphical structure of complex environments with a swarm of robots},
  isbn = {978-1-5090-4633-1},
  url = {http://ieeexplore.ieee.org/document/7989174/},
  abstract = {This paper presents a novel multi-robot mapping algorithm which allows a large number of simple robots to map the discrete graphical structure underlying an environment of multiple disjoint subregions. Examples of such environments include rooms in a building, buildings in a town, chambers in a cave network, or islands in an archipelago. Each robot is limited to a small communication range, compass, GPS sensor, and a short-range proximity sensor (e.g. bump sensor). Furthermore memory is limited, so no metric map of the environment is stored. Instead the algorithm determines which robots inhabit the same subregion, and which of these groups of robots are able to communicate. This information is captured in a disk graph representation. It is proven that these simple capabilities are sufficient to guarantee that all agents will determine the graphical structure in a finite time. Two environment configurations were tested with a range of quantities of robots. These simulations confirm that processing time is polynomial in the number of robots and indicate that the number of steps to convergence is linear in the number of robots.},
  language = {en},
  urldate = {2020-07-21},
  booktitle = {2017 {IEEE} {International} {Conference} on {Robotics} and {Automation} ({ICRA})},
  publisher = {IEEE},
  author = {Caccavale, Adam and Schwager, Mac},
  month = may,
  year = {2017},
  keywords = {mapping},
  pages = {1459--1466},
  month_numeric = {5}
}