Rashmi Singh, D. K. Nishad, Saifullah Khalid, Aryan Chaudhary
{"title":"A review of the application of fuzzy mathematical algorithm-based approach in autonomous vehicles and drones","authors":"Rashmi Singh, D. K. Nishad, Saifullah Khalid, Aryan Chaudhary","doi":"10.1007/s41315-024-00385-4","DOIUrl":null,"url":null,"abstract":"<p>Autonomous vehicles (AVs) and unmanned aerial vehicles (UAVs) have brought about transformative changes in transportation and aviation. However, making these systems fully autonomous and able to navigate safely in unpredictable real-world situations remains a big challenge. Fuzzy logic and related mathematical algorithms have emerged as practical tools to tackle uncertainty and complex decision-making in these systems. This paper reviews how fuzzy logic and mathematical approaches are applied in areas like navigation, control, avoiding obstacles, planning routes, and decision-making for AVs and UAVs. It delves into the key methods, designs, pros, and cons of using fuzzy logic in autonomous vehicles. The paper also compares fuzzy logic with other AI techniques. The review shows that fuzzy logic manages the uncertainties and imprecision involved in how autonomous vehicles perceive and navigate dynamic environments. Fuzzy controllers often perform better than traditional methods in vehicle control and UAV direction control. High-level decisions and route planning in AVs have also benefited from fuzzy inference systems. Still, challenges like computational efficiency, adaptability, and integrating fuzzy logic with other AI components remain. The paper concludes with suggestions for future research to make autonomous vehicles and drones smarter and safer using fuzzy logic. This review is a useful guide for anyone developing intelligent autonomous systems.</p>","PeriodicalId":44563,"journal":{"name":"International Journal of Intelligent Robotics and Applications","volume":null,"pages":null},"PeriodicalIF":2.1000,"publicationDate":"2024-09-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Intelligent Robotics and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s41315-024-00385-4","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ROBOTICS","Score":null,"Total":0}
引用次数: 0
Abstract
Autonomous vehicles (AVs) and unmanned aerial vehicles (UAVs) have brought about transformative changes in transportation and aviation. However, making these systems fully autonomous and able to navigate safely in unpredictable real-world situations remains a big challenge. Fuzzy logic and related mathematical algorithms have emerged as practical tools to tackle uncertainty and complex decision-making in these systems. This paper reviews how fuzzy logic and mathematical approaches are applied in areas like navigation, control, avoiding obstacles, planning routes, and decision-making for AVs and UAVs. It delves into the key methods, designs, pros, and cons of using fuzzy logic in autonomous vehicles. The paper also compares fuzzy logic with other AI techniques. The review shows that fuzzy logic manages the uncertainties and imprecision involved in how autonomous vehicles perceive and navigate dynamic environments. Fuzzy controllers often perform better than traditional methods in vehicle control and UAV direction control. High-level decisions and route planning in AVs have also benefited from fuzzy inference systems. Still, challenges like computational efficiency, adaptability, and integrating fuzzy logic with other AI components remain. The paper concludes with suggestions for future research to make autonomous vehicles and drones smarter and safer using fuzzy logic. This review is a useful guide for anyone developing intelligent autonomous systems.
期刊介绍:
The International Journal of Intelligent Robotics and Applications (IJIRA) fosters the dissemination of new discoveries and novel technologies that advance developments in robotics and their broad applications. This journal provides a publication and communication platform for all robotics topics, from the theoretical fundamentals and technological advances to various applications including manufacturing, space vehicles, biomedical systems and automobiles, data-storage devices, healthcare systems, home appliances, and intelligent highways. IJIRA welcomes contributions from researchers, professionals and industrial practitioners. It publishes original, high-quality and previously unpublished research papers, brief reports, and critical reviews. Specific areas of interest include, but are not limited to:Advanced actuators and sensorsCollective and social robots Computing, communication and controlDesign, modeling and prototypingHuman and robot interactionMachine learning and intelligenceMobile robots and intelligent autonomous systemsMulti-sensor fusion and perceptionPlanning, navigation and localizationRobot intelligence, learning and linguisticsRobotic vision, recognition and reconstructionBio-mechatronics and roboticsCloud and Swarm roboticsCognitive and neuro roboticsExploration and security roboticsHealthcare, medical and assistive roboticsRobotics for intelligent manufacturingService, social and entertainment roboticsSpace and underwater robotsNovel and emerging applications