Fuzzy Logic Guidance Control Systems for Autonomous Navigation Based on Omnidirectional Sensing

Hernández, Danilo Cáceres; Hoang, Vu; Filonenko, Alexander; Jo, Kang-Hyun

doi:10.1007/978-3-319-07455-9_44

Cited by 3 publications

(2 citation statements)

References 9 publications

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“…The density-based spatial clustering of applications with noise (DBSCAN) method was applied to mobile robots in [43,44]. It was applied for vanishing point estimation based on the data registered with the use of an omnidirectional camera installed onboard a wheeled mobile robot.…”

Section: Unsupervised Learning For Obstacle Avoidance and Path Planningmentioning

confidence: 99%

A Survey of Machine Learning Approaches for Mobile Robot Control

Rybczak,

Popowniak,

Lazarowska

2024

Robotics

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Machine learning (ML) is a branch of artificial intelligence that has been developing at a dynamic pace in recent years. ML is also linked with Big Data, which are huge datasets that need special tools and approaches to process them. ML algorithms make use of data to learn how to perform specific tasks or make appropriate decisions. This paper presents a comprehensive survey of recent ML approaches that have been applied to the task of mobile robot control, and they are divided into the following: supervised learning, unsupervised learning, and reinforcement learning. The distinction of ML methods applied to wheeled mobile robots and to walking robots is also presented in the paper. The strengths and weaknesses of the compared methods are formulated, and future prospects are proposed. The results of the carried out literature review enable one to state the ML methods that have been applied to different tasks, such as the following: position estimation, environment mapping, SLAM, terrain classification, obstacle avoidance, path following, learning to walk, and multirobot coordination. The survey allowed us to associate the most commonly used ML algorithms with mobile robotic tasks. There still exist many open questions and challenges such as the following: complex ML algorithms and limited computational resources on board a mobile robot; decision making and motion control in real time; the adaptability of the algorithms to changing environments; the acquisition of large volumes of valuable data; and the assurance of safety and reliability of a robot’s operation. The development of ML algorithms for nature-inspired walking robots also seems to be a challenging research issue as there exists a very limited amount of such solutions in the recent literature.

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Section: Unsupervised Learning For Obstacle Avoidance and Path Planningmentioning

confidence: 99%

A Survey of Machine Learning Approaches for Mobile Robot Control

Rybczak,

Popowniak,

Lazarowska

2024

Robotics

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“…In [38,39], a navigation approach was developed using a single omni-directional camera. This approach was based on the robot positioning within parallel features, e.g., road lanes.…”

Section: Mobile Robots Head Estimation Using Vanish Pointsmentioning

confidence: 99%

Position Estimation of Mobile Robots Using Omni-Directional Cameras

Fouad¹

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Mobile robots are prospected to significantly improve the efficiency and productivity of individuals. However, to fulfil their required tasks, they must be able to efficiently manoeuvre in their surrounding environments. This requirement necessitates that these robots posses the ability to acquire their current position and orientation within their work space. To acquire this information, mobile robots need precise and reliable perception techniques. Different perception methods has been described in Before beginning, I am extremely grateful to Allah for allowing me to reach this point in pursuing my goals. I am also extremely thankful for my supervisors Professor Jie Liu and Professor Jurek Sasiadek for their continuous support and encouragement along the Masters' journey. I am also thankful for my colleagues in the research lab for their encouragement and insightful suggestions for improving this work.

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Mobile robot for power substation inspection: a survey

Zhang

2017

IEEE/CAA J. Autom. Sinica

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Fuzzy Logic Guidance Control Systems for Autonomous Navigation Based on Omnidirectional Sensing

Cited by 3 publications

References 9 publications

A Survey of Machine Learning Approaches for Mobile Robot Control

A Survey of Machine Learning Approaches for Mobile Robot Control

Position Estimation of Mobile Robots Using Omni-Directional Cameras

Mobile robot for power substation inspection: a survey

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