A cooperative approach to avoiding obstacles and collisions between autonomous industrial vehicles in a simulation platform

IF 5.8 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Integrated Computer-Aided Engineering Pub Date : 2022-10-24 DOI:10.3233/ica-220694
J. Grosset, A. Ndao, A. Fougères, M. Djoko-Kouam, C. Couturier, J. Bonnin
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引用次数: 1

Abstract

Industry 4.0 leads to a strong digitalization of industrial processes, but also a significant increase in communication and cooperation between the machines that make it up. This is the case with autonomous industrial vehicles (AIVs) and other cooperative mobile robots which are multiplying in factories, often in the form of fleets of vehicles, and whose intelligence and autonomy are increasing. While the autonomy of autonomous vehicles has been well characterized in the field of road and road transport, this is not the case for the autonomous vehicles used in industry. The establishment and deployment of AIV fleets raises several challenges, all of which depend on the actual level of autonomy of the AIVs: acceptance by employees, vehicle location, traffic fluidity, collision detection, or vehicle perception of changing environments. Thus, simulation serves to account for the constraints and requirements formulated by the manufacturers and future users of AIVs. In this paper, after having proposed a broad state of the art on the problems to be solved in order to simulate AIVs before proceeding to experiments in real conditions, we present a method to estimate positions of AIVs moving in a closed industrial environment, the extension of a collision detection algorithm to deal with the obstacle avoidance issue, and the development of an agent-based simulation platform for simulating these two methods and algorithms. The resulting/final/subsequent simulation will allow us to experiment in real conditions.
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仿真平台中自动驾驶工业车辆之间障碍物和碰撞的协同避障方法
工业4.0带来了工业过程的强大数字化,但也显著增加了组成工业过程的机器之间的通信和合作。自动工业车辆(aiv)和其他协作式移动机器人就是这种情况,它们在工厂中数量激增,通常以车队的形式出现,其智能和自主性正在增强。虽然自动驾驶汽车的自主性已经在道路和道路运输领域得到了很好的体现,但在工业领域使用的自动驾驶汽车却并非如此。自动驾驶汽车车队的建立和部署带来了几个挑战,所有这些挑战都取决于自动驾驶汽车的实际自主水平:员工的接受程度、车辆位置、交通流动性、碰撞检测或车辆对变化环境的感知。因此,仿真有助于解释aiv制造商和未来用户制定的约束和要求。在本文中,在提出了仿真aiv需要解决的问题的广泛现状之后,我们提出了一种在封闭工业环境中估计aiv移动位置的方法,扩展了碰撞检测算法来处理避障问题,并开发了一个基于agent的仿真平台来模拟这两种方法和算法。由此产生的/最终的/随后的模拟将使我们能够在真实条件下进行实验。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Integrated Computer-Aided Engineering
Integrated Computer-Aided Engineering 工程技术-工程:综合
CiteScore
9.90
自引率
21.50%
发文量
21
审稿时长
>12 weeks
期刊介绍: Integrated Computer-Aided Engineering (ICAE) was founded in 1993. "Based on the premise that interdisciplinary thinking and synergistic collaboration of disciplines can solve complex problems, open new frontiers, and lead to true innovations and breakthroughs, the cornerstone of industrial competitiveness and advancement of the society" as noted in the inaugural issue of the journal. The focus of ICAE is the integration of leading edge and emerging computer and information technologies for innovative solution of engineering problems. The journal fosters interdisciplinary research and presents a unique forum for innovative computer-aided engineering. It also publishes novel industrial applications of CAE, thus helping to bring new computational paradigms from research labs and classrooms to reality. Areas covered by the journal include (but are not limited to) artificial intelligence, advanced signal processing, biologically inspired computing, cognitive modeling, concurrent engineering, database management, distributed computing, evolutionary computing, fuzzy logic, genetic algorithms, geometric modeling, intelligent and adaptive systems, internet-based technologies, knowledge discovery and engineering, machine learning, mechatronics, mobile computing, multimedia technologies, networking, neural network computing, object-oriented systems, optimization and search, parallel processing, robotics virtual reality, and visualization techniques.
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