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Related Experiment Video

Updated: Nov 18, 2025

The Modular Design and Production of an Intelligent Robot Based on a Closed-Loop Control Strategy
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An Optimal Footprint Based Coverage Planning for Hydro Blasting Robots.

Thejus Pathmakumar1, Madan Mohan Rayguru1, Sriharsha Ghanta1

  • 1Engineering Product Development Pillar, Singapore University of Technology and Design, Singapore 487372, Singapore.

Sensors (Basel, Switzerland)
|February 11, 2021
PubMed
Summary
This summary is machine-generated.

Automating industrial hydro blasting with robots is crucial. This study optimizes robot footprint using a genetic algorithm to minimize blasting time and energy, validated on the Hornbill robot.

Keywords:
coverage planninghydro blasting robotmulti-objective optimizationoptimal footprint

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Area of Science:

  • Robotics and Automation
  • Industrial Maintenance
  • Optimization Techniques

Background:

  • Hydro blasting is vital for industrial metallic surface maintenance but is labor-intensive and time-consuming.
  • Current mobile robots for hydro blasting may be inefficient due to suboptimal footprint selection.
  • Automating hydro blasting requires efficient area coverage and task execution.

Purpose of the Study:

  • To propose a multi-objective optimization framework for determining the optimal sweeping angle of a hydro blasting robot's arm.
  • To minimize both blasting time and energy consumption simultaneously.
  • To enhance the efficiency of automated hydro blasting operations.

Main Methods:

  • Utilizing the robot's blasting arm sweeping angle as its effective footprint.
  • Employing a multi-objective optimization framework.
  • Applying the genetic algorithm (GA) to compute the optimal sweeping arc for minimizing time and energy.

Main Results:

  • Numerical simulations demonstrated the effectiveness of the proposed optimization approach.
  • The genetic algorithm successfully identified optimal sweeping arcs.
  • The strategy was implemented on the Hornbill hydro blasting robot, confirming its efficacy through experimental trials.

Conclusions:

  • The proposed optimization framework effectively determines the optimal robot footprint for hydro blasting.
  • Using the sweeping angle as the footprint and GA optimization significantly reduces blasting time and energy.
  • The successful experimental validation on the Hornbill robot confirms the practical applicability and efficiency of the developed strategy.