Search Results - (( _ navigation learning algorithm ) OR ( java implication based algorithm ))

Advancements and challenges in mobile robot navigation: a comprehensive review of algorithms and potential for self-learning approaches by Al Mahmud, Suaib, Kamarulariffin, Abdurrahman, Mohd Ibrahim, Azhar, Haja Mohideen, Ahmad Jazlan

“…In this review paper, a comprehensive review of mobile robot navigation algorithms has been conducted. The findings suggest that, even though the self-learning algorithms require huge amounts of training data and have the possibility of learning erroneous behavior, they possess huge potential to overcome challenges rarely addressed by the other traditional algorithms. …”
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Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview by Ejaz, M.M., Tang, T.B., Lu, C.-K.

“…Reinforcement Learning (RL) algorithm with deep learning techniques helps to solve many complex problems of today's world, such as to play a video game and autonomous navigation in the robots using the raw image as an input. …”
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Autonomous Visual Navigation using Deep Reinforcement Learning: An Overview by Ejaz, M.M., Tang, T.B., Lu, C.-K.

“…Reinforcement Learning (RL) algorithm with deep learning techniques helps to solve many complex problems of today's world, such as to play a video game and autonomous navigation in the robots using the raw image as an input. …”
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Development of algorithm for improved maze navigation by Ahmad, Faiz Aydil

“…This paper describes the development of algorithm for improved maze navigation and it is a continuation on a previous project. …”
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A novel navigation algorithm for collaborative multi robots by Ahmed, Mohiuddin, Khan, Md. Raisuddin, Billah, Md. Masum, Farhana, Soheli

“…The goal of multi-agent robots is to move as a cohesive team by sharing their distributed learning behaviors and navigating in autonomous reconnaissance missions. …”
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A Review: Current Trend of Immersive Technologies for Indoor Navigation and the Algorithms by Sariman, Muhammad Shazmin, Othman, Maisara, Mat Akir, Rohaida, Mahamad, Abd Kadir, Ab Rahman, Munirah

“…Based on the findings of this review, we can conclude that an efficient solution for indoor navigation that uses the capabilities of embedded data and technological advances in immersive technologies can be achieved by training the shortest path algorithm with a deep learning algorithm to enhance the indoor navigation system.…”
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A collaborative navigation algorithm for multi-agent robots in autonomous reconnaissance mission by Ahmed, Mohiuddin, Khan, Md. Raisuddin, Billah, Md. Masum, Farhana, Soheli

“…The goal of multi-agent robots is to move as a cohesive team by sharing their distributed learning behaviors and navigating in autonomous reconnaissance missions. …”
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Dynamic path planning algorithm in mobile robot navigation by Yun, S.C., Parasuraman, S., Ganapathy, V.

“…In this research, Genetic Algorithm (GA) is used to assist mobile robot to move, identify the obstacles in the environment, learn the environment and reach the desired goal in an unknown and unrecognized environment. …”
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IMPLEMENTATION OF BEHAVIOUR BASED NAVIGATION IN A PHYSICALLY CONFINED SITE by ABDUL RAZAK, NUSRAH

“…Behaviour-based architecture is one of the most effective autonomous navigation techniques, second only to machine learning. …”
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A Modified Hybrid Fuzzy Controller for Real-Time Mobile Robot Navigation by Hossen J., Sayeed S., Iqbal A.K.M.P.

“…Algorithms; Controllers; Fuzzy clustering; Fuzzy systems; Intelligent control; Intelligent systems; Learning algorithms; Least squares approximations; Membership functions; Mobile robots; Navigation; Robotics; Robots; Smart sensors; and ANFIS; Apriori algorithms; Fuzzy C mean; Gradient descent algorithms; Hybrid-fuzzy controllers; Mobile Robot Navigation; Subtractive clustering; Subtractive clustering algorithms; Clustering algorithms…”

Collision prediction based genetic network programming-reinforcement learning for mobile robot navigation in unknown dynamic environments by Findi, Ahmed H. M., Marhaban, Mohammad Hamiruce, Raja Ahmad, Raja Mohd Kamil, Hassan, Mohd Khair

“…Genetic Network Programming with Reinforcement Learning (GNP-RL) has several important features over other evolutionary algorithms such as it combines offline and online learning on the one hand, and it combines diversified and intensified search on the other hand, but it was used in solving the problem of MR navigation in static environment only. …”
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Solving robot path planning problem using Ant Colony Optimisation (ACO) approach / Nordin Abu Bakar and Rosnawati Abdul Kudus by Abu Bakar, Nordin, Abdul Kudus, Rosnawati

“…These experimental scenarios represent the respective navigation frameworks found in the literature used to test learning algorithms. …”
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Advancing mobile robot navigation with DRL and heuristic rewards: a comprehensive review by Khan, Mazbahur Rahman, Mohd Ibrahim, Azhar, Al Mahmud, Suaib, Samat, Farah Asyiqin, Jasni, Farahiyah, Mardzuki, Muhammad Imran

“…The advent of Deep Reinforcement Learning (DRL) has spurred significant research into enabling mobile robots to learn effective navigation by optimizing actions based on environmental rewards. …”
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Adaptive route optimization for mobile robot navigation using evolutionary algorithm by Kit Guan Lim, Guan Lim, Yoong Hean Lee, Hean Lee, Min Keng Tan, Keng Tan, Hou, Pin Yoong, Tienlei, Wang, Tze, Kenneth Kin Teo

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A modified Q-learning path planning approach using distortion concept and optimization in dynamic environment for autonomous mobile robot by Low, Ee Soong, Ong, Pauline, Low, Cheng Yee

“…Autonomous mobile robot path planning in unknown and dynamic environment is a crucial task for successful mobile robot navigation. This study proposes an improved Q-learning (IQL) algorithm to address the challenges of path planning in such environments. …”
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A modified Q-learning path planning approach using distortion concept and optimization in dynamic environment for autonomous mobile robot by Ee Soong Low, Ee Soong Low, Pauline Ong, Pauline Ong, Cheng Yee Low, Cheng Yee Low

“…Autonomous mobile robot path planning in unknown and dynamic environment is a crucial task for successful mobile robot navigation. This study proposes an improved Q-learning (IQL) algorithm to address the challenges of path planning in such environments. …”
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Prediction of stroke disease using machine learning techniques / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Warris, Saiful Nizam, Abu Bakar, Mohd Saifulnizam, Kadar, Rozita

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A modified Q-learning path planning approach using distortion concept and optimization in dynamic environment for autonomous mobile robot by Ee Soong Low, Ee Soong Low, Pauline Ong, Pauline Ong, Cheng Yee Low, Cheng Yee Low

“…Autonomous mobile robot path planning in unknown and dynamic environment is a crucial task for successful mobile robot navigation. This study proposes an improved Q-learning (IQL) algorithm to address the challenges of path planning in such environments. …”
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Design and Implementation of a Robot for Maze-Solving using Flood-Fill Algorithm by Elshamarka, Ibrahim, Saman, Abu Bakar Sayuti

“…Algorithm for straight-line correction was based on PI(D) controller. …”
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Deep Learning-Based Geomagnetic Navigation Method Integrated with Dead Reckoning by Yan, Suqing, Su, Yalan, Luo, Xiaonan, Sun, Anqing, Ji, Yuanfa, Kamarul Hawari, Ghazali

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