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Applied Sciences, 2022 Intelligent mobile robots that can move independently were laid out in the real world around 100 years ago during the second world war after advancements in computer science.
R. Raj, A. Kos
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Mobile Robot Path Planning in Dynamic Environments Through Globally Guided Reinforcement Learning [PDF]
IEEE Robotics and Automation Letters, 2020 Path planning for mobile robots in large dynamic environments is a challenging problem, as the robots are required to efficiently reach their given goals while simultaneously avoiding potential conflicts with other robots or dynamic objects.
Binyu Wang +3 more
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Deep reinforcement learning based mobile robot navigation: A review
, 2021 : Navigation is a fundamental problem of mobile robots, for which Deep Reinforcement Learning (DRL) has received significant attention because of its strong representation and experience learning abilities.
Kai Zhu, Tao Zhang
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A Lifelong Learning Approach to Mobile Robot Navigation
IEEE Robotics and Automation Letters, 2021 This letter presents a self-improving lifelong learning framework for a mobile robot navigating in different environments. Classical static navigation methods require environment-specific in-situ system adjustment, e.g., from human experts, or may repeat
Bo Liu, Xuesu Xiao, P. Stone
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A Review on Challenges of Autonomous Mobile Robot and Sensor Fusion Methods
IEEE Access, 2020 Autonomous mobile robots are becoming more prominent in recent time because of their relevance and applications to the world today. Their ability to navigate in an environment without a need for physical or electro-mechanical guidance devices has made it
Mary B. Alatise, G. Hancke
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Wireless Communications and Mobile Computing, 2021 Several research studies are conducted based on the control of wheeled mobile robots. Nonholonomy constraints associated with wheeled mobile robots have encouraged the development of highly nonlinear control techniques.
Hua Cen, B. Singh
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Learning to automatically detect features for mobile robots using second-order Hidden Markov Models [PDF]
, 2002 In this paper, we propose a new method based on Hidden Markov Models to interpret temporal sequences of sensor data from mobile robots to automatically detect features.
Aycard, Olivier +2 more
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Italian National Conference on Sensors, 2020 Planning an optimal path for a mobile robot is a complicated problem as it allows the mobile robots to navigate autonomously by following the safest and shortest path between starting and goal points. The present work deals with the design of intelligent
Fatin Hassan Ajeil +3 more
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Mobile Robot Self-Localization with 2D Push-Broom LIDAR in a 2D Map [PDF]
, 2020 This paper proposes mobile robot self-localization based on an onboard 2D push-broom (or tilted-down) LIDAR using a reference 2D map previously obtained with a 2D horizontal LIDAR.
Clotet Bellmunt, Eduard +3 more
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Gas Source Localization Strategies for Teleoperated Mobile Robots. An Experimental Analysis [PDF]
, 2017 Gas source localization (GSL) is one of the most important and direct applications of a gas sensitive mobile robot, and consists in searching for one or multiple volatile emission sources with a mobile robot that has improved sensing capabilities (i.e.
Gongora, Andres +2 more
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