Coverage Path Planning and Precise Localization for Autonomous Lawn Mowers
by , , , , , , , ,
Abstract:
In this paper, we present a concept for automatic path planning and high-precision localization for autonomous lawn mowers. In particular, two objectives contribute to the increased efficiency of the presented approach compared to classical automatic lawn mowing techniques. First, the standard chaotic control of the mower is replaced by an efficient planning strategy for traversing the area without gaps and with as few overlaps as possible. Second, the conventional boundary wires become unnecessary as high-precision localization based on multi-sensor fusion allows for keeping the virtual boundaries. The whole concept is implemented and tested on an industrial-grade lawn mower. The advantages of intelligent path planning over chaotic strategies are shown, and the localization performance is validated using real-world data.
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PDF URL: https://ieeexplore.ieee.org/document/10023754
Reference:
Coverage Path Planning and Precise Localization for Autonomous Lawn Mowers (Maria Höffmann, Joachim Clemens, David Stronzek-Pfeifer, Ruggero Simonelli, Andreas Serov, Sven Schettino, Margareta Runge, Kerstin Schill, Christof Büskens), In 6th IEEE International Conference on Robotic Computing (IRC), 2022.
Bibtex Entry:
@INPROCEEDINGS{hoeffmann2022coverage,
  author={Höffmann, Maria and Clemens, Joachim and Stronzek-Pfeifer, David and Simonelli, Ruggero and Serov, Andreas and Schettino, Sven and Runge, Margareta and Schill, Kerstin and Büskens, Christof},
  booktitle={6th IEEE International Conference on Robotic Computing (IRC)},
  title={Coverage Path Planning and Precise Localization for Autonomous Lawn Mowers},
  year={2022},
  pages={238-242},
  doi={10.1109/IRC55401.2022.00046},
	url={https://ieeexplore.ieee.org/document/10023754},
	keywords={startnow},
	abstract={In this paper, we present a concept for automatic path planning and high-precision localization for autonomous lawn mowers. In particular, two objectives contribute to the increased efficiency of the presented approach compared to classical automatic lawn mowing techniques. First, the standard chaotic control of the mower is replaced by an efficient planning strategy for traversing the area without gaps and with as few overlaps as possible. Second, the conventional boundary wires become unnecessary as high-precision localization based on multi-sensor fusion allows for keeping the virtual boundaries. The whole concept is implemented and tested on an industrial-grade lawn mower. The advantages of intelligent path planning over chaotic strategies are shown, and the localization performance is validated using real-world data.}
}