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.

Simulation of robotic inspections based on systematic data acquisition and analysis

Rea P.;
2025-01-01

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.
2025
Mobile Robots; Modelling; Obstacle Detection; Simulation; Systematic Data Analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/443626
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