Agent-Oriented Modelling and Simulation for Robotic Based Predator Control - Andy, Yee Wee Chieh; Shiang, Cheah Wai; Paschal, Celine Haren (Society of Visual Informatics, 2025)
Agent-oriented modeling (AOM) is a methodology that can develop complex tasks that involve multi-agent system development, such as robotic systems. There are still insufficient studies on how Agent-Oriented Modelling benefits robotic development. There is little reference to using Agent-Oriented Modelling to develop complex systems, especially robotic applications. This study aims to investigate the adoption of AOM for robotic surveillance modeling and simulation for predator control in the farming sector and to conduct qualitative comparisons on robotic models and simulation methods. A case study of robotic-based predator control is used to develop the system using the AOM model. Later, this is incorporated into a Netlogo simulation to illustrate the suggested methodology in the model simulation stage. A qualitative analysis of the model is performed to validate the model. SUS analysis for AOM usability at the score of 68.35 shows AOM is at the average usability level for beginner users in software development. Qualitative analysis shows that beginner users prefer to use AOM for complex adaptive and distributed robotic systems. AOM is introduced to create robotic-based predator control in a structured manner to prove that AOM can be used to develop complex systems. Introducing Agent-Oriented Modelling in various domains leads to higher confidence in the industry player's adoption of this model across multiple system developments.