Model‐Based Engineering with Application to Autonomy

Bhadani, Rahul; Bunting, Matt; Sprinkle, Jonathan

doi:10.1002/9781119552482.ch10

Cited by 1 publication

(1 citation statement)

References 44 publications

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“…4,5 Simulation is an easier and faster way to perform robotics experiments. According to Bhadani et al, 6 modeling and simulation (M&S) are essential tools for meeting the challenges of complexity in cyber-physical systems (CPS). These challenges revolve around the complex interaction of physical and computational components within these systems.…”

Section: Introductionmentioning

confidence: 99%

An integrated Design Methodology for Swarm Robotics using Model-Based Systems Engineering and Robot Operating System

Aloui,

Guizani,

Hammadi

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part C:

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In swarm robotics, robots solve problems using collective behaviors similar to those observed in natural systems, such as birds, bees or fish. They determine their collective behavior through several simple interactions. However, the behavior of swarms emerging from local interactions remains difficult to predict. When trying to design swarm robotic systems for real applications, researchers are confronted with a wide range of software and hardware challenges in the different phases of the design process; problems related to the modeling of swarm systems, related to simulation, related to implementation on software and even on real systems, etc. Despite the increasing popularity of swarm robotics, designing effective and scalable swarm systems remains a challenging task due to the complex interactions between the individual robots and the environment. Therefore, there is a need for a systematic and comprehensive methodology that can guide designers in developing swarm robotics systems that are efficient, reliable, and adaptable to different scenarios. Our main contribution is to propose a new integrated methodology for the development of swarm robot systems. This methodology is based on modeling with Model-Based Systems Engineering method (MBSE) to specify the requirements and the collective behaviors of the swarms, then on the verification of the developed models and finally on the validation of the swarm system by physical prototyping with real robots. Our contribution also focuses on the development of a new SysML profile using the Domain Specific Language (DSL) that we call SwarmML to customize the functional and structural modeling of a swarm system (properties and attributes of the swarm). Two case studies are applied to validate our methodology; a case study of an aggregation of a swarm of robots and a case study of a collaborative simultaneous localization and mapping application (C-SLAM) performed by a swarm of Turtlebots. The novelty of this proposed methodology is the combination of SysML and Robot Operating System (ROS) to address the management of traceability between the different levels of swarm system design, in order to achieve functional, physical and software integration.

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Section: Introductionmentioning

confidence: 99%