GK-ANFIS:用于机器人路径规划的门控和kan增强自适应神经模糊推理系统

IF 5.9 2区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Guanyuan Feng, Meiqi Zhou, Weili Shi, Yu Miao
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引用次数: 0

摘要

未知环境下的自主导航对现代智能系统至关重要。然而,现有算法分别解决路径规划和避障问题,导致优先级冲突、路径长度过大和死锁风险。此外,固定的成员功能限制了系统的灵活性。本文提出了一种由三个关键模块组成的新型端到端框架——GK-ANFIS。首先,利用特征融合模块解决路径规划与避障之间的冲突;其次,采用门控模块自适应调整目标导向权值,降低死锁风险。最后,引入自适应隶属函数模块,增强数据拟合能力和系统灵活性。CoppeliaSim上的大量实验表明,GK-ANFIS优于传统的ANFIS, RMSE降低了92.63%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
GK-ANFIS: Gated and KAN-enhanced adaptive neuro-fuzzy inference system for robot path planning
Autonomous navigation in unknown environments is critical for modern intelligent systems. However, existing algorithms separately address path planning and obstacle avoidance, causing priority conflicts, excessive path lengths, and deadlock risks. Additionally, fixed membership functions limit system flexibility. This paper presents GK-ANFIS, a novel end-to-end framework consisting of three key modules. Firstly, a feature fusion module to resolve conflicts between path planning and obstacle avoidance. Secondly, a gating module to adaptively adjust target-guiding weights and mitigate deadlock risks. Lastly, an adaptive membership function module to enhance data fitting and system flexibility. Extensive experiments on CoppeliaSim show that GK-ANFIS outperforms traditional ANFIS, reducing RMSE by 92.63%.
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来源期刊
Ain Shams Engineering Journal
Ain Shams Engineering Journal Engineering-General Engineering
CiteScore
10.80
自引率
13.30%
发文量
441
审稿时长
49 weeks
期刊介绍: in Shams Engineering Journal is an international journal devoted to publication of peer reviewed original high-quality research papers and review papers in both traditional topics and those of emerging science and technology. Areas of both theoretical and fundamental interest as well as those concerning industrial applications, emerging instrumental techniques and those which have some practical application to an aspect of human endeavor, such as the preservation of the environment, health, waste disposal are welcome. The overall focus is on original and rigorous scientific research results which have generic significance. Ain Shams Engineering Journal focuses upon aspects of mechanical engineering, electrical engineering, civil engineering, chemical engineering, petroleum engineering, environmental engineering, architectural and urban planning engineering. Papers in which knowledge from other disciplines is integrated with engineering are especially welcome like nanotechnology, material sciences, and computational methods as well as applied basic sciences: engineering mathematics, physics and chemistry.
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