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A Quantum-Based Collaborative Guidance Strategy for Multirobot Plume Source Localization

  • Rui Guo Li
  • , Huai Ning Wu*
  • *Corresponding author for this work
  • Tiangong University
  • Peng Cheng Laboratory

Research output: Contribution to journal › Article › peer-review

Abstract

In combination with optimization theory and swarm evolutionary mechanisms, based on multiple mobile robots equipped with sensors, this article deals with a plume source localization issue with information fusion, environmental obstacles, and communication restrictions for robots. First of all, combined with information fusion, in terms of collision avoidance and communication restrictions between robots, the source localization issue can be addressed by solving a path planning one with constraints for cooperative swarm robots, which is transformed into an unconstrained one by an information penalty policy. Second, after a quantum potential well is coupled, two pairs of average estimators and minimum estimators are introduced into swarm evolutionary mechanisms with a knowledge-driven protocol and an adjustable oscillation weight, and the distributed quantum-inspired guidance (DQIG) strategy as a guidance scheme is proposed to drive the robots toward the plume source. Subsequently, we put forth a formation behavior consisting of leader-follower mechanisms, obstacle avoidance mechanisms, motion optimization mechanisms and target encircling mechanisms, which not only provides a practical collision/obstacle measure, but also increases the coverage area for the target. Afterward, a performance analysis for the proposed policy is executed on the convergence and computational complexity, which ensures the accuracy and timeliness of the source localization in theory. Ultimately, simulation verification is carried out, and the results validate the practicability and effectiveness of the developed method.

Original languageEnglish
Pages (from-to)938-950
Number of pages13
JournalIEEE Transactions on Control of Network Systems
Volume11
Issue number2
DOIs
StatePublished - 1 Jun 2024

Keywords

  • Computational complexity
  • convergence property
  • distributed quantum-inspired guidance (DQIG) strategy
  • formation behavior
  • plume source localization
  • swarm robots

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