An Efficient Approach for Line-Following Automated Guided Vehicles Based on Fuzzy Inference Mechanism

Bach, Sy-Hung; Yi, Soo-Yeong

doi:10.18196/jrc.v3i4.14787

Cited by 9 publications

(4 citation statements)

References 29 publications

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“…Additionally, public awareness and acceptance of these technologies play a very important role for the prevention of vehicle collision. Rather than VANET, fuzzy Logics are utilized to prevent vehicle collisions involves creating a decision-making system that assesses the risk of collision based on various input parameters and takes appropriate actions to avoid or mitigate the collision [7]. Here is a step-by-step guide on how to implement a collision prevention system using Fuzzy Logic: 3) Membership functions and fuzzy rules: Assign membership functions to each fuzzy set.…”

Section: ) Traffic Management and Congestion Reductionmentioning

confidence: 99%

An Efficient and Intelligent System for Controlling the Speed of Vehicle using Fuzzy Logic and Deep Learning

Yadav,

Goyal

2024

IJACSA

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Vehicle collisions are a significant problem worldwide, causing injuries, fatalities, and property damage. There are several reasons for the collapse of vehicles such as rash driving, over speeding, less driving skills, increasing number of vehicles, drunk and drive, etc. However, over speeding is one of the critical factors out of all the reasons for vehicle collisions. To address the critical issues, the current article proposes a Fuzzybased algorithm to prevent and control the speed of the vehicle. The major objective of the proposed system is to control the speed of the vehicle for proactive collision avoidance. Deep learning and fuzzy system provide better integrated approach for the controlling of the speed and avoid vehicle collision. Fuzzification of the speed variable provides an advanced or viable solution for speed control. The current research used RNN and other deep learning algorithm to predict the traffic and identify the traffic frequency. The traffic frequency in a timeseries frame provides the frequency of the traffic within a time frame that can be detected by using involvement of IoT.

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Section: ) Traffic Management and Congestion Reductionmentioning

confidence: 99%

An Efficient and Intelligent System for Controlling the Speed of Vehicle using Fuzzy Logic and Deep Learning

Yadav,

Goyal

2024

IJACSA

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“…One of the possibilities is to focus on cooperation between AGVs and humans, which is settled in a dynamic environment and changes over time [64,70,72,84,85,92]. Human experience [56,[58][59][60][61][62][63]65,80,82] is considered in these cases. To describe this cooperation, the authors used the following: • HMI-human-machine interference [66,73].…”

Section: Human-agv Cooperationmentioning

confidence: 99%

“…A similar approach was presented in the research prepared by [108], where AGVs could anticipate human behaviors and predict their trajectory because human movements are usually directly motivated by their tasks. In [62], a controller was proposed, which mimics the standards of human vehicle control, for example, "situation-aware speed adjustment on curved paths". Prati et al adopted a human-centered approach to prepare a set of guidelines with details on information exchange between humans and robots.…”

Section: Human-agv Cooperationmentioning

confidence: 99%

Interaction between a Human and an AGV System in a Shared Workspace—A Literature Review Identifying Research Areas

Tubis,

Poturaj,

Smok

2024

Sustainability

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Background: This article presents the results of a literature review from 2018 to 2023, which focused on research related to human and AGV system cooperation in a shared workspace. This study defines AGV systems as systems using Automated Guided Vehicles or Autonomous Guided Vehicles. An Automated Guided Vehicle is a cart that follows a guided path, while an Autonomous Guided Vehicle is an Automated Guided Vehicle that is autonomously controlled. The analyses conducted answered two research questions: (RQ1) In what aspects are the human factor examined in publications on the implementation and operation of AGV systems? (RQ2) Has the human-AGV collaboration aspect been analyzed in the context of a sustainable work environment? Methods: The literature review was conducted following the systematic literature review method, using the PRISMA approach. Results: Based on the search of two journal databases, according to the indicated keywords, 1219 documents pertaining to the analyzed issues were identified. The selection and elimination of documents that did not meet the defined criteria made it possible to limit the number of publications to 117 articles and proceedings papers. On this basis, the authors defined a classification framework comprising five basic research categories and nine subcategories. The analyzed documents were classified, and each distinguished group was characterized by describing the results. Conclusions: The development of a two-level classification framework for research from the analyzed area according to the assumptions of the concept map and the identification of research gaps in the area of human-AGV interaction.

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“…In recent years, the self-driving technology has been a great development [27][28][29][30]. Recently, such technology was also utilized in electric wheelchairs.…”

Section: Introductionmentioning

confidence: 99%

Electric Wheelchair Hybrid Operating System Coordinated with Working Range of a Robotic Arm

Yang

Guo

Sakamoto

et al. 2022

Journal of Robotics and Control

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Electric wheelchair-mounted robotic arms can help patients with disabilities to perform their activities in daily living (ADL). Joysticks or keypads are commonly used as the operating interface of Wheelchair-mounted robotic arms. Under different scenarios, some patients with upper limb disabilities such as finger contracture cannot operate such interfaces smoothly. Recently, manual interfaces for different symptoms to operate the wheelchair-mounted robotic arms are being developed. However, the stop the wheelchairs in an appropriate position for the robotic arm grasping task is still not easy. To reduce the individual’s burden in operating wheelchair in narrow spaces and to ensure that the chair always stops within the working range of a robotic arm, we propose here an operating system for an electric wheelchair that can automatically drive itself to within the working range of a robotic arm by capturing the position of an AR marker via a chair-mounted camera. Meanwhile, the system includes an error correction model to correct the wheelchair’s moving error. Finally, we demonstrate the effectiveness of the proposed system by running the wheelchair and simulating the robotic arm through several courses.

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An Efficient Approach for Line-Following Automated Guided Vehicles Based on Fuzzy Inference Mechanism

Cited by 9 publications

References 29 publications

An Efficient and Intelligent System for Controlling the Speed of Vehicle using Fuzzy Logic and Deep Learning

An Efficient and Intelligent System for Controlling the Speed of Vehicle using Fuzzy Logic and Deep Learning

Interaction between a Human and an AGV System in a Shared Workspace—A Literature Review Identifying Research Areas

Electric Wheelchair Hybrid Operating System Coordinated with Working Range of a Robotic Arm

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