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An Embodied Intelligence-Based Biologically Inspired Strategy for Searching a Moving Target.

Julian K P Tan1, Chee Pin Tan2, Surya G Nurzaman3

  • 1Monash University Malaysia, School of Engineering. JulianKPTan787@gmail.com.

Artificial Life
|July 26, 2022
PubMed
Summary

This study introduces a novel search strategy inspired by bacterial chemotaxis and embodied intelligence. It demonstrates how sensory sensitivity and random walk strategies enhance robot search effectiveness, even without environmental gradients.

Keywords:
Bacterial chemotaxisbiological fluctuationembodied intelligencemobile robotrandom search

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Area of Science:

  • Robotics
  • Biomimetics
  • Artificial Intelligence

Background:

  • Bacterial chemotaxis in Escherichia coli uses tumbling and swimming to navigate gradients.
  • Recent research suggests random walk strategies can guide behavior without environmental gradients.
  • Embodied intelligence emphasizes the interaction between an agent's morphology, sensory systems, and environment.

Purpose of the Study:

  • To present a minimalistic, biologically inspired search strategy based on bacterial chemotaxis and embodied intelligence.
  • To investigate the role of sensory sensitivity and inherent random walk strategies in search effectiveness.
  • To explore search behavior with and without gradient information using a biological fluctuation framework.

Main Methods:

  • Simulated a single-sensor mobile robot searching for a moving target.
  • Implemented bacterial chemotaxis-inspired search behaviors.
  • Utilized a biological fluctuation framework to model noise in behavior.
  • Compared search effectiveness across different random walk strategies: Ballistic, Levy, Brownian, and Stationary.

Main Results:

  • Search effectiveness is significantly influenced by sensory sensitivity.
  • Inherent random walk strategies (Ballistic, Levy, Brownian, Stationary) impact search performance.
  • The study demonstrates the viability of gradient-free search strategies.
  • Embodied intelligence principles are crucial for optimizing search behavior.

Conclusions:

  • A minimalistic, biologically inspired search strategy can be effective.
  • Sensory sensitivity and inherent random walk patterns are key determinants of search success.
  • Embodied intelligence plays a vital role in optimizing search strategies, even in simple systems.