An Exploration-Enhanced Search Algorithm for Robot Indoor Source Searching

Miao Wang, Bin Xin*, Mengjie Jing, Yun Qu

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

Abstract

Chemical, biological, or radioactive substances may be released in accidents, posing a threat to human life and property. Due to the dense obstacles and specific structures of indoor environments, indoor source searching still faces challenges, such as the initial position of the robot cannot be placed freely, the source may not be in the airflow, and most areas indoors lack concentration and airflow clues. This study proposes an exploration-enhanced search algorithm, enabling the robot to search for a source located downstream of the robot or outside the airflow in an indoor environment with a narrow plume without losing the classic upstream search ability. The algorithm equips the robot with the capability to search for a source in complex indoor environments where measurements frequently change. The algorithm is evaluated in the simulated environment to assess the contributions of its components and its performance under different airflow speeds. The algorithm is also compared with the state-of-the-art algorithms and shows superior performance. The effectiveness of the algorithm is further demonstrated in real-world environments.

Original languageEnglish
Pages (from-to)4160-4178
Number of pages19
JournalIEEE Transactions on Robotics
Volume40
DOIs
Publication statusPublished - 2024

Keywords

  • Frontier-based exploration
  • indoor
  • rapidly-exploring random trees (RRTs)
  • robot
  • source searching

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