Efficient Communication and Navigation for Soccer Robots using a Time Petri net Model

13 pages•Published: March 21, 2024

Shane Chiovarou, Madison Bland and Seung-yun Kim

Abstract

Robotics is a very expansive and ever-growing field that allows for a large number of different scenarios to occur. Once application is coordination of multiple robots in a single system, and that is highlighted in an environment such as RoboCup competitions. The Contextual Communication and Navigation (CCN) Algorithm is an approach to the problem of multiple robots coordinating at a common goal through the lens of Communication and Navigation. A scheme of communication that allows Nao Robots to efficiently communicate their positions using the minimal number of bits to transfer data was designed as well as a navigation scheme that allows robots to use the information they have on other robots to navigate to a goal. The CCN Algorithm was simulated and tested along with Dijkstra and A* in order to compare the effectiveness of each of the algorithms in tackling this problem and it was found that the CCN Algorithm was the most efficient.

Keyphrases: communication, petri nets, robot navigation, timed petri nets

In: Ajay Bandi, Mohammad Hossain and Ying Jin (editors). Proceedings of 39th International Conference on Computers and Their Applications, vol 98, pages 116-128.

Links:	https://easychair.org/publications/paper/N6GM
	https://doi.org/10.29007/ndb7

BibTeX entry

@inproceedings{CATA2024:Efficient_Communication_Navigation_Soccer,
  author    = {Shane Chiovarou and Madison Bland and Seung-yun Kim},
  title     = {Efficient Communication and Navigation for Soccer Robots using a Time Petri net Model},
  booktitle = {Proceedings of 39th International Conference on Computers and Their Applications},
  editor    = {Ajay Bandi and Mohammad Hossain and Ying Jin},
  series    = {EPiC Series in Computing},
  volume    = {98},
  publisher = {EasyChair},
  bibsource = {EasyChair, https://easychair.org},
  issn      = {2398-7340},
  url       = {/publications/paper/N6GM},
  doi       = {10.29007/ndb7},
  pages     = {116-128},
  year      = {2024}}

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