Simulation Software in the Design and AI-Driven Automation of All-Terrain Farm Vehicles and Implements for Precision Agriculture DOI Creative Commons
Mrutyunjay Padhiary,

Prodipto Roy,

Kundan Kumar

и другие.

Опубликована: Апрель 1, 2025

Precision agriculture depends on the automation and mechanization of agricultural equipment vehicles in a variety terrains, which increases productivity sustainability. This review presents comparative analysis significant simulation software used designing developing automated systems, emphasizing their methodologies significance advancing farm technology. Artificial intelligence (AI) machine learning (ML) methods are modeled, optimized, integrated using key technologies such as MATLAB/Simulink, SolidWorks, ANSYS, AirSim, Gazebo. The results demonstrate how these improve automation's real-time decision-making, predictive maintenance, system accuracy. Case studies illustrate practical application simulating all-terrain specialized implements. best tools for autonomous navigation AirSim Gazebo, although MATLAB/Simulink is particularly adept at system-level AI modeling. study takes new approach to improving design, control, environmental interactions by combining many modeling tools. makes it easier make systems that last longer work better. It suggested future investigate relationship between automation, AI, greater detail propel precision forward.

Язык: Английский

Simulation Software in the Design and AI-Driven Automation of All-Terrain Farm Vehicles and Implements for Precision Agriculture DOI Creative Commons
Mrutyunjay Padhiary,

Prodipto Roy,

Kundan Kumar

и другие.

Опубликована: Апрель 1, 2025

Precision agriculture depends on the automation and mechanization of agricultural equipment vehicles in a variety terrains, which increases productivity sustainability. This review presents comparative analysis significant simulation software used designing developing automated systems, emphasizing their methodologies significance advancing farm technology. Artificial intelligence (AI) machine learning (ML) methods are modeled, optimized, integrated using key technologies such as MATLAB/Simulink, SolidWorks, ANSYS, AirSim, Gazebo. The results demonstrate how these improve automation's real-time decision-making, predictive maintenance, system accuracy. Case studies illustrate practical application simulating all-terrain specialized implements. best tools for autonomous navigation AirSim Gazebo, although MATLAB/Simulink is particularly adept at system-level AI modeling. study takes new approach to improving design, control, environmental interactions by combining many modeling tools. makes it easier make systems that last longer work better. It suggested future investigate relationship between automation, AI, greater detail propel precision forward.

Язык: Английский

Процитировано

0