Simulation of Robotic Inspections Based on Systematic Data Acquisition and Analysis

Autonomous robots are of utmost importance across various research fields and have numerous practical applications. They can be used in scenarios such as rescue operations, security, safety management, and interventions in hazardous or hostile environments, among others. A key application of these robots is overcoming obstacles in extreme conditions, especially when human intervention is either impossible or not permitted. This paper presents modelling and simulation results based on a mathematical tool developed through systematic data acquisition and analysis, ensuring the safe operation of a robot designed to assist its pilot. The proposed predictive model is built using data collected from the robot's sensors, which are stored in a dedicated database. This data includes information on position, velocity, and acceleration, as well as their handling and processing in the presence of obstacles. The paper also includes a case study, with results that can serve as a predictive model applicable to similar conditions.

Authors

Publication Details

Journal
International Journal of Simulation Modelling
Published
2025-03-02
DOI
https://doi.org/10.2507/ijsimm24-1-708
Citations
4
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
4.97
Controls
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Simulation of Robotic Inspections Based on Systematic Data Acquisition and Analysis

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International Journal of Simulation Modelling
Industrial Vision Systems and Defect Detection
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article

Simulation of Robotic Inspections Based on Systematic Data Acquisition and Analysis

Hélio Lopes, José Machado, Pierluigi Rea, Edward Kozłowski, Erika Ottaviano, Katarzyna Antosz
article en
4 citations

Abstract

Autonomous robots are of utmost importance across various research fields and have numerous practical applications. They can be used in scenarios such as rescue operations, security, safety management, and interventions in hazardous or hostile environments, among others. A key application of these robots is overcoming obstacles in extreme conditions, especially when human intervention is either impossible or not permitted. This paper presents modelling and simulation results based on a mathematical tool developed through systematic data acquisition and analysis, ensuring the safe operation of a robot designed to assist its pilot. The proposed predictive model is built using data collected from the robot's sensors, which are stored in a dedicated database. This data includes information on position, velocity, and acceleration, as well as their handling and processing in the presence of obstacles. The paper also includes a case study, with results that can serve as a predictive model applicable to similar conditions.

International Journal of Simulation ModellingVol. 24(1)
Openalex Percentile: Top 6%
Industrial Vision Systems and Defect Detection
4.97
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