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A bio-inspired localization-free stochastic coverage algorithm with verified reachability.

Ayesha Khan1, Said Al-Abri1, Vivek Mishra1

  • 1Georgia Institute of Technology, North Ave NW, Atlanta, GA 30332, United States of America.

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Summary
This summary is machine-generated.

Mobile robots can now explore unknown areas without GPS using a novel Persistent Turning Walker (PTW) strategy. This bio-inspired random search method offers faster coverage than traditional models in GPS-denied environments.

Keywords:
Markov chainsarea coveragebio inspired algorithmsfish behaviormobile roboticspersistent turning Walker

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Area of Science:

  • Robotics
  • Artificial Intelligence
  • Bio-inspired algorithms

Background:

  • Mobile robots often rely on external localization services like GPS, which are unreliable or unavailable in many environments.
  • Achieving efficient area coverage in unknown, GPS-denied spaces is a significant challenge for autonomous systems.

Purpose of the Study:

  • To develop a novel coverage strategy for mobile robots that does not require external localization services.
  • To adapt a biological motion model, the Persistent Turning Walker (PTW), for robust 2D and 3D environmental exploration.

Main Methods:

  • The continuous-time Persistent Turning Walker (PTW) dynamical system was converted into a discrete-time Markov chain.
  • The strongly connected properties of the Markov chain were verified using numerical methods.
  • The PTW model's performance was analytically and statistically compared against Simple Random Walks (SRW) and Correlated Random Walks (CRW).

Main Results:

  • The proposed PTW algorithm demonstrated faster search-space coverage compared to SRW and CRW models.
  • The discrete-time Markov chain representation of PTW exhibited verifiable strongly connected properties.
  • Simulation results and statistical tests confirmed the superior performance of the PTW strategy.

Conclusions:

  • The Persistent Turning Walker (PTW) strategy provides an effective, localization-free method for mobile robot coverage in unknown environments.
  • This bio-inspired approach is particularly suitable for underwater, underground, or other GPS-denied operational scenarios.
  • The framework can potentially be extended to analyze other biological systems and their dynamics.