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A flooding algorithm for multirobot exploration.

Flavio Cabrera-Mora1, Jizhong Xiao

  • 1Department of Electrical Engineering, The Graduate Center, The City University of New York, New York, NY 10016, USA. fcabrera-mora@gc.cuny.edu

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society
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This summary is machine-generated.

This study introduces a decentralized multirobot exploration algorithm that uses landmarks to coordinate robot movement, significantly reducing exploration time and travel distance in tree-like environments.

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Distributed Systems

Background:

  • Efficient multirobot exploration is crucial for tasks like mapping and search and rescue.
  • Existing algorithms often face challenges in coordination and minimizing traversal distances.
  • Decentralized approaches are desirable for scalability and robustness.

Purpose of the Study:

  • To present a novel decentralized multirobot exploration algorithm.
  • To reduce exploration time and minimize overall robot traverse distance.
  • To analyze and evaluate the algorithm's performance on tree environments.

Main Methods:

  • Modeling the environment as a tree structure.
  • Implementing a coordination model restricting robots on edges and vertices.
  • Utilizing decentralized active landmarks dropped by robots at explored vertices.
  • Mathematical analysis of algorithm properties and exploration time bounds on trees.

Main Results:

  • The proposed algorithm effectively coordinates robot movement for efficient exploration.
  • Mathematical analysis provides bounds on exploration time for tree environments.
  • Defined three performance metrics for multirobot algorithms.
  • Simulations demonstrate competitive or superior performance compared to multirobot depth-first search (MR-DFS) and single-robot DFS.

Conclusions:

  • The decentralized landmark-based coordination algorithm offers an effective solution for multirobot exploration.
  • The algorithm demonstrates significant improvements in exploration efficiency.
  • The findings provide valuable insights for the design of future multirobot systems.